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Automatic fovea detection and choroid segmentation for choroidal thickness assessment in optical coherence tomography
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作者 Chen Yu Lin Hung Ju Chen +3 位作者 Yi Kit Chan Wei Ping Hsia Yu Len Huang Chia Jen Chang 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2024年第10期1763-1771,共9页
AIM:To develop an automated model for subfoveal choroidal thickness(SFCT)detection in optical coherence tomography(OCT)images,addressing manual fovea location and choroidal contour challenges.METHODS:Two procedures we... AIM:To develop an automated model for subfoveal choroidal thickness(SFCT)detection in optical coherence tomography(OCT)images,addressing manual fovea location and choroidal contour challenges.METHODS:Two procedures were proposed:defining the fovea and segmenting the choroid.Fovea localization from B-scan OCT image sequence with three-dimensional reconstruction(LocBscan-3D)predicted fovea location using central foveal depression features,and fovea localization from two-dimensional en-face OCT(LocEN-2D)used a mask region-based convolutional neural network(Mask R-CNN)model for optic disc detection,and determined the fovea location based on optic disc relative position.Choroid segmentation also employed Mask R-CNN.RESULTS:For 53 eyes in 28 healthy subjects,LocBscan-3D’s mean difference between manual and predicted fovea locations was 170.0μm,LocEN-2D yielded 675.9μm.LocEN-2D performed better in non-high myopia group(P=0.02).SFCT measurements from Mask R-CNN aligned with manual values.CONCLUSION:Our models accurately predict SFCT in OCT images.LocBscan-3D excels in precise fovea localization even with high myopia.LocEN-2D shows high detection rates but lower accuracy especially in the high myopia group.Combining both models offers a robust SFCT assessment approach,promising efficiency and accuracy for large-scale studies and clinical use. 展开更多
关键词 subfoveal choroidal thickness optical coherence tomography automatic foveal detection automatic choroid segmentation
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A review of automatic detection of epilepsy based on EEG signals
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作者 Qirui Ren Xiaofan Sun +6 位作者 Xiangqu Fu Shuaidi Zhang Yiyang Yuan Hao Wu Xiaoran Li Xinghua Wang Feng Zhang 《Journal of Semiconductors》 EI CAS CSCD 2023年第12期8-30,共23页
Epilepsy is a common neurological disorder that occurs at all ages.Epilepsy not only brings physical pain to patients,but also brings a huge burden to the lives of patients and their families.At present,epilepsy detec... Epilepsy is a common neurological disorder that occurs at all ages.Epilepsy not only brings physical pain to patients,but also brings a huge burden to the lives of patients and their families.At present,epilepsy detection is still achieved through the observation of electroencephalography(EEG)by medical staff.However,this process takes a long time and consumes energy,which will create a huge workload to medical staff.Therefore,it is particularly important to realize the automatic detection of epilepsy.This paper introduces,in detail,the overall framework of EEG-based automatic epilepsy identification and the typical methods involved in each step.Aiming at the core modules,that is,signal acquisition analog front end(AFE),feature extraction and classifier selection,method summary and theoretical explanation are carried out.Finally,the future research directions in the field of automatic detection of epilepsy are prospected. 展开更多
关键词 EPILEPSY ELECTROENCEPHALOGRAPHY automatic detection analog front end feature extraction CLASSIFIER
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Automatic Diagnosis of Polycystic Ovarian Syndrome Using Wrapper Methodology with Deep Learning Techniques
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作者 Mohamed Abouhawwash S.Sridevi +3 位作者 Suma Christal Mary Sundararajan Rohit Pachlor Faten Khalid Karim Doaa Sami Khafaga 《Computer Systems Science & Engineering》 SCIE EI 2023年第10期239-253,共15页
One of the significant health issues affecting women that impacts their fertility and results in serious health concerns is Polycystic ovarian syndrome(PCOS).Consequently,timely screening of polycystic ovarian syndrom... One of the significant health issues affecting women that impacts their fertility and results in serious health concerns is Polycystic ovarian syndrome(PCOS).Consequently,timely screening of polycystic ovarian syndrome can help in the process of recovery.Finding a method to aid doctors in this procedure was crucial due to the difficulties in detecting this condition.This research aimed to determine whether it is possible to optimize the detection of PCOS utilizing Deep Learning algorithms and methodologies.Additionally,feature selection methods that produce the most important subset of features can speed up calculation and enhance the effectiveness of classifiers.In this research,the tri-stage wrapper method is used because it reduces the computation time.The proposed study for the Automatic diagnosis of PCOS contains preprocessing,data normalization,feature selection,and classification.A dataset with 39 characteristics,including metabolism,neuroimaging,hormones,and biochemical information for 541 subjects,was employed in this scenario.To start,this research pre-processed the information.Next for feature selection,a tri-stage wrapper method such as Mutual Information,ReliefF,Chi-Square,and Xvariance is used.Then,various classification methods are tested and trained.Deep learning techniques including convolutional neural network(CNN),multi-layer perceptron(MLP),Recurrent neural network(RNN),and Bi long short-term memory(Bi-LSTM)are utilized for categorization.The experimental finding demonstrates that with effective feature extraction process using tri stage wrapper method+CNN delivers the highest precision(97%),high accuracy(98.67%),and recall(89%)when compared with other machine learning algorithms. 展开更多
关键词 Deep learning automatic detection polycystic ovarian syndrome tri-stage wrapper method mutual information RELIEF CHI-SQUARE
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An automatic seismic signal detection method based on fourth-order statistics and applications 被引量:2
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作者 刘希强 蔡寅 +4 位作者 赵瑞 曲保安 赵银刚 冯志军 李红 《Applied Geophysics》 SCIE CSCD 2014年第2期128-138,252,共12页
Real-time, automatic, and accurate determination of seismic signals is critical for rapid earthquake reporting and early warning. In this study, we present a correction trigger function(CTF) for automatically detect... Real-time, automatic, and accurate determination of seismic signals is critical for rapid earthquake reporting and early warning. In this study, we present a correction trigger function(CTF) for automatically detecting regional seismic events and a fourth-order statistics algorithm with the Akaike information criterion(AIC) for determining the direct wave phase, based on the differences, or changes, in energy, frequency, and amplitude of the direct P- or S-waves signal and noise. Simulations suggest for that the proposed fourth-order statistics result in high resolution even for weak signal and noise variations at different amplitude, frequency, and polarization characteristics. To improve the precision of establishing the S-waves onset, first a specific segment of P-wave seismograms is selected and the polarization characteristics of the data are obtained. Second, the S-wave seismograms that contained the specific segment of P-wave seismograms are analyzed by S-wave polarization filtering. Finally, the S-wave phase onset times are estimated. The proposed algorithm was used to analyze regional earthquake data from the Shandong Seismic Network. The results suggest that compared with conventional methods, the proposed algorithm greatly decreased false and missed earthquake triggers, and improved the detection precision of direct P- and S-wave phases. 展开更多
关键词 Seismic signal P and S-waves automatic detection correction trigger function
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An automatic detection of green tide using multi-windows with their adaptive threshold from Landsat TM/ETM plus image 被引量:4
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作者 WANG Changying CHU Jialan +3 位作者 TAN Meng SHAO Fengjing SUI Yi LI Shujing 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2017年第11期106-114,共9页
Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of... Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of green tide is presented from Landsat TM/ETM plus image which needs not the atmospheric correction. In order to achieve an automatic detection of green tide, a linear relationship(y =0.723 x+0.504) between detection threshold y and subtraction x(x=λnir–λred) is found from the comparing Landsat TM/ETM plus image with the field surveys.Using this relationship, green tide patches can be detected automatically from Landsat TM/ETM plus image.Considering there is brightness difference between different regions in an image, the image will be divided into a plurality of windows(sub-images) with a same size firstly, and then each window will be detected using an adaptive detection threshold determined according to the discovered linear relationship. It is found that big errors will appear in some windows, such as those covered by clouds seriously. To solve this problem, the moving step k of windows is proposed to be less than the window width n. Using this mechanism, most pixels will be detected[n/k]×[n/k] times except the boundary pixels, then every pixel will be assigned the final class(green tide or sea water) according to majority rule voting strategy. It can be seen from the experiments, the proposed detection method using multi-windows and their adaptive thresholds can detect green tide from Landsat TM/ETM plus image automatically. Meanwhile, it avoids the reliance on the accurate atmospheric correction. 展开更多
关键词 automatic detection green tide adaptive threshold Landsat TM/ETM plus image
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A detailed investigation of low latitude tweek atmospherics observed by the WHU ELF/VLF receiver:Ⅰ. Automatic detection and analysis method 被引量:12
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作者 RuoXian Zhou XuDong Gu +8 位作者 KeXin Yang GuangSheng Li BinBin Ni Juan Yi Long Chen FuTai Zhao ZhengYu Zhao Qi Wang LiQing Zhou 《Earth and Planetary Physics》 CSCD 2020年第2期120-130,共11页
As a dispersive wave mode produced by lightning strokes, tweek atmospherics provide important hints of lower ionospheric(i.e., D-region) electron density. Based on data accumulation from the WHU ELF/VLF receiver syste... As a dispersive wave mode produced by lightning strokes, tweek atmospherics provide important hints of lower ionospheric(i.e., D-region) electron density. Based on data accumulation from the WHU ELF/VLF receiver system, we develop an automatic detection module in terms of the maximum-entropy-spectral-estimation(MESE) method to identify unambiguous instances of low latitude tweeks.We justify the feasibility of our procedure through a detailed analysis of the data observed at the Suizhou Station(31.57°N, 113.32°E) on17 February 2016. A total of 3961 tweeks were registered by visual inspection;the automatic detection method captured 4342 tweeks, of which 3361 were correct ones, producing a correctness percentage of 77.4%(= 3361/4342) and a false alarm rate of 22.6%(= 981/4342).A Short-Time Fourier Transformation(STFT) was also applied to trace the power spectral profiles of identified tweeks and to evaluate the tweek propagation distance. It is found that the fitting accuracy of the frequency–time curve and the relative difference of propagation distance between the two methods through the slope and through the intercept can be used to further improve the accuracy of automatic tweek identification. We suggest that our automatic tweek detection and analysis method therefore supplies a valuable means to investigate features of low latitude tweek atmospherics and associated ionospheric parameters comprehensively. 展开更多
关键词 tweeks automatic detection WHU-VLF receiver
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Pavement Cracks Coupled With Shadows:A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach 被引量:2
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作者 Lili Fan Shen Li +3 位作者 Ying Li Bai Li Dongpu Cao Fei-Yue Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2023年第7期1593-1607,共15页
Automatic pavement crack detection is a critical task for maintaining the pavement stability and driving safety.The task is challenging because the shadows on the pavement may have similar intensity with the crack,whi... Automatic pavement crack detection is a critical task for maintaining the pavement stability and driving safety.The task is challenging because the shadows on the pavement may have similar intensity with the crack,which interfere with the crack detection performance.Till to the present,there still lacks efficient algorithm models and training datasets to deal with the interference brought by the shadows.To fill in the gap,we made several contributions as follows.First,we proposed a new pavement shadow and crack dataset,which contains a variety of shadow and pavement pixel size combinations.It also covers all common cracks(linear cracks and network cracks),placing higher demands on crack detection methods.Second,we designed a two-step shadow-removal-oriented crack detection approach:SROCD,which improves the performance of the algorithm by first removing the shadow and then detecting it.In addition to shadows,the method can cope with other noise disturbances.Third,we explored the mechanism of how shadows affect crack detection.Based on this mechanism,we propose a data augmentation method based on the difference in brightness values,which can adapt to brightness changes caused by seasonal and weather changes.Finally,we introduced a residual feature augmentation algorithm to detect small cracks that can predict sudden disasters,and the algorithm improves the performance of the model overall.We compare our method with the state-of-the-art methods on existing pavement crack datasets and the shadow-crack dataset,and the experimental results demonstrate the superiority of our method. 展开更多
关键词 automatic pavement crack detection data augmentation compensation deep learning residual feature augmentation shadow removal shadow-crack dataset
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Quick and automatic detection of co-seismic landslides with multifeature deep learning model
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作者 Wenchao HUANGFU Haijun QIU +5 位作者 Peng CUI Dongdong YANG Ya LIU Bingzhe TANG Zijing LIU Mohib ULLAH 《Science China Earth Sciences》 SCIE EI CAS CSCD 2024年第7期2311-2325,共15页
Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics simila... Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics similar to those of co-seismic landslides,making it difficult to gather information and assess their impact rapidly and accurately.Therefore,an automatic detection method based on a deep learning model,named ENVINet5,with multiple features(ENVINet5_MF)was proposed to solve this problem and improve the detection accuracy of co-seismic landslides.The ENVINet5_MF method is advantageous for co-seismic landslide detection because it features a landslide gain index(LGI)that effectively eliminates the spectral interference of bare land and roads.We conducted two experiments using multi-temporal PlanetScope images acquired in Hokkaido,Japan,and Mainling,China.The accuracy evaluation and rationality analysis show that ENVINet5_MF performed better than comparative methods and that the co-seismic landslide areas detected by ENVINet5_MF were the most consistent with ground reference data.The findings of this study suggest that ENVINet5_MF can provide an efficient and accurate method for coseismic landslide detection to ensure a rapid response to co-seismic landslide disasters. 展开更多
关键词 Co-seismic landslide automatic detection Deep learning Landslide gain index PlanetScope images
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Cow-YOLO:Automatic cow mounting detection based on non-local CSPDarknet53 and multiscale neck
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作者 De Li Junhao Wang +5 位作者 Zhe Zhang Baisheng Dai Kaixuan Zhao Weizheng Shen Yanling Yin Yang Li 《International Journal of Agricultural and Biological Engineering》 SCIE 2024年第3期193-202,共10页
Cows mounting behavior is a significant manifestation of estrus in cows.The timely detection of cows mounting behavior can make cows conceive in time,thereby improving milk production of cows and economic benefits of ... Cows mounting behavior is a significant manifestation of estrus in cows.The timely detection of cows mounting behavior can make cows conceive in time,thereby improving milk production of cows and economic benefits of the pasture.Existing methods of mounting behavior detection are difficult to achieve precise detection under occlusion and severe scale change environments and meet real-time requirements.Therefore,this study proposed a Cow-YOLO model to detect cows mounting behavior.To meet the needs of real-time performance,YOLOv5s model is used as the baseline model.In order to solve the problem of difficult detection of cows mounting behavior in an occluded environment,the CSPDarknet53 of YOLOv5s is replaced with Non-local CSPDarknet53,which enables the network to obtain global information and improves the model’s ability to detect the mounting cows.Next,the neck of YOLOv5s is redesigned to Multiscale Neck,reinforcing the multi-scale feature fusion capability of model to solve difficulty detection under dramatic scale changes.Then,to further increase the detection accuracy,the Coordinate Attention Head is integrated into YOLOv5s.Finally,these improvements form a novel cow mounting detection model called Cow-YOLO and make Cow-YOLO more suitable for cows mounting behavior detection in occluded and drastic scale changes environments.Cow-YOLO achieved a precision of 99.7%,a recall of 99.5%,a mean average precision of 99.5%,and a detection speed of 156.3 f/s on the test set.Compared with existing detection methods of cows mounting behavior,Cow-YOLO achieved higher detection accuracy and faster detection speed in an occluded and drastic scale-change environment.Cow-YOLO can assist ranch breeders in achieving real-time monitoring of cows estrus,enhancing ranch economic efficiency. 展开更多
关键词 cows mounting automatic detection Cow-YOLO computer vision CSPDarknet53 multiscale neck
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Automatic detection method of bladder tumor cells based on color and shape features
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作者 Zitong Zhao Yanbo Wang +6 位作者 Jiaqi Chen Mingjia Wang Shulong Feng Jin Yang Nan Song Jinyu Wang Ci Sun 《Journal of Innovative Optical Health Sciences》 SCIE EI 2024年第6期1-13,共13页
Bladder urothelial carcinoma is the most common malignant tumor disease in urinary system,and its incidence rate ranks ninth in the world.In recent years,the continuous development of hyperspectral imaging technology ... Bladder urothelial carcinoma is the most common malignant tumor disease in urinary system,and its incidence rate ranks ninth in the world.In recent years,the continuous development of hyperspectral imaging technology has provided a new tool for the auxiliary diagnosis of bladder cancer.In this study,based on microscopic hyperspectral data,an automatic detection algorithm of bladder tumor cells combining color features and shape features is proposed.Support vector machine(SVM)is used to build classification models and compare the classification performance of spectral feature,spectral and shape fusion feature,and the fusion feature proposed in this paper on the same classifier.The results show that the sensitivity,specificity,and accuracy of our classification algorithm based on shape and color fusion features are 0.952,0.897,and 0.920,respectively,which are better than the classification algorithm only using spectral features.Therefore,this study can effectively extract the cell features of bladder urothelial carcinoma smear,thus achieving automatic,real-time,and noninvasive detection of bladder tumor cells,and then helping doctors improve the efficiency of pathological diagnosis of bladder urothelial cancer,and providing a reliable basis for doctors to choose treatment plans and judge the prognosis of the disease. 展开更多
关键词 Bladder tumor cells microscopic hyperspectral fusion feature support vector machine automatic detection.
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Precision orchard sprayer based on automatically infrared target detecting and electrostatic spraying techniques 被引量:18
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作者 He Xiongkui Zeng Aijun +1 位作者 Liu Yajia Song Jianli 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2011年第1期35-40,共6页
There is an urgent need for new chemical application techniques and sprayers in Chinese orchard spraying.A new tractor-mounted automatic target detecting electrostatics,and air-assisted orchard sprayer was designed an... There is an urgent need for new chemical application techniques and sprayers in Chinese orchard spraying.A new tractor-mounted automatic target detecting electrostatics,and air-assisted orchard sprayer was designed and developed to meet the demand of chemical pest control in orchards.This sprayer light weighted,highly efficient,reduces pesticide use and is friendly to the environment.The techniques of automatic target detecting,electrostatics,and air-assisted spraying were combined in this system.The electrostatically charged droplets are projected toward the target by the assistance of an air stream that increases the droplets penetration within canopy.Experimental results show that the new automatic target detecting orchard sprayer with an infrared sensor can save more than 50%to 75%of pesticides,improve the utilization rate(over 55%),control efficiency,and significantly reduce environmental pollution caused by the pesticide application.At the same time the key technological problems related to air-assisted low volume and electrostatic spraying were solved. 展开更多
关键词 precision spraying orchard sprayer automatic target plant detection air assisted spray electrostatic spray
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Approximate entropy and support vector machines for electroencephalogram signal classification 被引量:3
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作者 Zhen Zhang Yi Zhou +3 位作者 Ziyi Chen Xianghua Tian Shouhong Du Ruimei Huang 《Neural Regeneration Research》 SCIE CAS CSCD 2013年第20期1844-1852,共9页
The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate ... The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate entropy and a support vector machine that has strong generalization ability were applied to classify electroencephalogram signals at epileptic interictal and ictal periods. Our aim was to verify whether approximate entropy waves can be effectively applied to the automatic real-time detection of epilepsy in the electroencephalogram, and to explore its generalization ability as a classifier trained using a nonlinear dynamics index. Four patients presenting with partial epileptic seizures were included in this study. They were all diagnosed with neocortex localized epilepsy and epileptic foci were clearly observed by electroencephalogram. The electroencephalogram data form the four involved patients were segmented and the characteristic values of each segment, that is, the approximate entropy, were extracted. The support vector machine classifier was constructed with the approximate entropy extracted from one epileptic case, and then electroencephalogram waves of the other three cases were classified, reaching a 93.33% accuracy rate. Our findings suggest that the use of approximate entropy allows the automatic real-time detection of electroencephalogram data in epileptic cases. The combination of approximate entropy and support vector machines shows good generalization ability for the classification of electroencephalogram signals for epilepsy. 展开更多
关键词 neural regeneration brain injury EPILEPSY ELECTROENCEPHALOGRAM nonlinear dynamics approximate entropy support vector machine automatic real-time detection classification GENERALIZATION grants-supported paper NEUROREGENERATION
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Auroral event detection using spatiotemporal statistics of local motion vectors 被引量:1
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作者 WANG Qian LIANG Jimin HU Zejun 《Advances in Polar Science》 2013年第3期175-182,共8页
The analysis and exploration of auroral dynamics are very significant for studying auroral mechanisms. This paper proposes a method based on auroral dynamic processes for detecting auroral events automatically. We fir... The analysis and exploration of auroral dynamics are very significant for studying auroral mechanisms. This paper proposes a method based on auroral dynamic processes for detecting auroral events automatically. We first obtained the motion fields using the multiscale fluid flow estimator. Then, the auroral video frame sequence was represented by the spatiotemporal statistics of local motion vectors. Finally, automatic auroral event detection was achieved. The experimental results show that our methods could detect the required auroral events effectively and accurately, and that the detections were independent on any specific auroral event. The proposed method makes it feasible to statistically analyze a large number of continuous observations based on the auroral dynamic process. 展开更多
关键词 automatic detection auroral event fluid flow
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Localized Coverage Connectivity Based on Shape and Area Using Mobile Sensor Robots in Wireless Sensor Networks 被引量:1
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作者 Rajaram Pichamuthu Prakasam Periasamy 《Circuits and Systems》 2016年第8期1962-1975,共15页
A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as... A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as battlefield inspection and biological detection. The Constrained Motion and Sensor (CMS) Model represents the features and explain k-step reach ability testing to describe the states. The description and calculation based on CMS model does not solve the problem in mobile robots. The ADD framework based on monitoring radio measurements creates a threshold. But the methods are not effective in dynamic coverage of complex environment. In this paper, a Localized Coverage based on Shape and Area Detection (LCSAD) Framework is developed to increase the dynamic coverage using mobile robots. To facilitate the measurement in mobile robots, two algorithms are designed to identify the coverage area, (i.e.,) the area of a coverage hole or not. The two algorithms are Localized Geometric Voronoi Hexagon (LGVH) and Acquaintance Area Hexagon (AAH). LGVH senses all the shapes and it is simple to show all the boundary area nodes. AAH based algorithm simply takes directional information by locating the area of local and global convex points of coverage area. Both these algorithms are applied to WSN of random topologies. The simulation result shows that the proposed LCSAD framework attains minimal energy utilization, lesser waiting time, and also achieves higher scalability, throughput, delivery rate and 8% maximal coverage connectivity in sensor network compared to state-of-art works. 展开更多
关键词 Localized Coverage Wireless Senor Network automatic Detection Framework Geometric Voronoi Polygon Acquaintance Area Polygons Environment Monitoring Mobile Sensor Robots
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An Infrared Touch System for Automatic Behavior Monitoring
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作者 Qingqing Liu Xing Yang +4 位作者 Ru Song Junying Su Moxuan Luo Jinling Zhong Liping Wang 《Neuroscience Bulletin》 SCIE CAS CSCD 2021年第6期815-830,共16页
Key requirements of successful animal behavior research in the laboratory are robustness,objectivity,and high throughput,which apply to both the recording and analysis of behavior.Many automatic methods of monitoring ... Key requirements of successful animal behavior research in the laboratory are robustness,objectivity,and high throughput,which apply to both the recording and analysis of behavior.Many automatic methods of monitoring animal behavior meet these requirements.However,they usually depend on high-performing hardware and sophisticated software,which may be expensive.Here,we describe an automatic infrared behavior-monitor(AIBM)system based on an infrared touchscreen frame.Using this,animal positions can be recorded and used for further behavioral analysis by any PC supporting touch events.This system detects animal behavior in real time and gives closed-loop feedback using relatively low computing resources and simple algorithms.The AIBM system automatically records and analyzes multiple types of animal behavior in a highly efficient,unbiased,and low-cost manner. 展开更多
关键词 automatic behavior detection Elevated plus maze Two-chamber Looming Foot-shock OPTOGENETICS Fiber photometry Heart rate and blood pressure
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微型计算机控制系统的可靠性分析
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作者 贾海 《郑州大学学报(理学版)》 CAS 1987年第2期31-33,共3页
目前国际上已广泛开展微机系统可靠性的研究,对控制系统进行可靠性设计。对于实时处理控制系统采用自动检测及容错设计技术,以提高系统的可靠性。假设某微机控制系统的可靠度为R(f),则该系统的失效率为F(t),即从0到t时刻内发生故障的概... 目前国际上已广泛开展微机系统可靠性的研究,对控制系统进行可靠性设计。对于实时处理控制系统采用自动检测及容错设计技术,以提高系统的可靠性。假设某微机控制系统的可靠度为R(f),则该系统的失效率为F(t),即从0到t时刻内发生故障的概率为F(t)=1-R(t)。 展开更多
关键词 automatic detection Fault—tolerant technique RELIABILITY Micno—computer.
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Particle Size Estimation Based on Edge Density 被引量:1
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作者 王卫星 《Journal of Electronic Science and Technology of China》 2005年第4期310-313,共4页
Given image sequences of closely packed particles, the underlying aim is to estimate diameters without explicit segmentation. In a way, this is similar to the task of counting objects without directly counting them. S... Given image sequences of closely packed particles, the underlying aim is to estimate diameters without explicit segmentation. In a way, this is similar to the task of counting objects without directly counting them. Such calculations may, for example, be useful)Cast estimation of particle size in different application areas. The topic is that of estimating average size (=average diameter) of packed particles, from formulas involving edge density, and the edges from moment-based thresholding are used. An average shape factor is involved in the calculations, obtained for some frames from crude partial segmentation. Measurement results from about 80frames have been analyzed. 展开更多
关键词 edge density average size particle images automatic particle inspection edge detection moment-based thresholding
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Research on Known Vulnerability Detection Method Based on Firmware Analysis
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作者 Wenjing Wang Tengteng Zhao +3 位作者 Xiaolong Li Lei Huang Wei Zhang Hui Guo 《Journal of Cyber Security》 2022年第1期1-15,共15页
At present,the network security situation is becoming more and more serious.Malicious network attacks such as computer viruses,Trojans and hacker attacks are becoming more and more rampant.National and group network a... At present,the network security situation is becoming more and more serious.Malicious network attacks such as computer viruses,Trojans and hacker attacks are becoming more and more rampant.National and group network attacks such as network information war and network terrorism have a serious damage to the production and life of the whole society.At the same time,with the rapid development of Internet of Things and the arrival of 5G era,IoT devices as an important part of industrial Internet system,have become an important target of infiltration attacks by hostile forces.This paper describes the challenges facing firmware vulnerability detection at this stage,and introduces four automatic detection and utilization technologies in detail:based on patch comparison,based on control flow,based on data flow and ROP attack against buffer vulnerabilities.On the basis of clarifying its core idea,main steps and experimental results,the limitations of its method are proposed.Finally,combined with four automatic detection methods,this paper summarizes the known vulnerability detection steps based on firmware analysis,and looks forward to the follow-up work. 展开更多
关键词 IoT devices vulnerability mining automatic detection static analysis
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People with Disabilities: Some Analyzes of the Results of the 2010 Population Census and New Challenges
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作者 Paulo Tadeu Meira e silva de Oliveira 《Journal of Mathematics and System Science》 2014年第4期231-243,共13页
In his work, was applied crossings between pairs of variables, homogeneity test and technical exhaustive AID (Automatic Interaction Detection) for formation of groups second sample each of the following deficiencies... In his work, was applied crossings between pairs of variables, homogeneity test and technical exhaustive AID (Automatic Interaction Detection) for formation of groups second sample each of the following deficiencies: see, listen, move and intellectual from database obtained from the 2010 Population Census data sample (respondents Complete Questionnaire) formed by 20,635,472 people interviewed all over the country with the objective of studying relationship between different variables such as disability, level of education, gender, income in minimum wages among others. 展开更多
关键词 Exhaustive automatic interaction detection homogeneity test homogeneous groups
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Gaussian Mixture Statistics Model Based on Automatic Inspection System Used in ITS
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作者 Xiaoqin Deng 《Journal of Systems Science and Information》 2006年第1期121-126,共6页
The ITS is becoming more and more important in the economic development of China. But most of the ITS used in Chinese major cities need the human to perform the supervision task. As a result, it consumes too much huma... The ITS is becoming more and more important in the economic development of China. But most of the ITS used in Chinese major cities need the human to perform the supervision task. As a result, it consumes too much human resources, and also can not achieve the satisfied supervision performance. Thus, in this paper, we will propose an automatic inspection system based on the Gaussian mixture statistics model to alleviate this kind of problem. The proposed method will utilize a Gaussian Mixture model to model the background, and then use the EM algorithm to update the model's coefficients frame by frame to make the model adapt to the changing environment. After successful modeling, we can extract out the foreground blocks from background blocks, and finally trigger the automatic alarming system by calculating the number of foreground blocks. From the experiment results, our proposed method can achieve considerable good results. 展开更多
关键词 ITS Gaussian mixture model EM algorithm automatic detection algorithm
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