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Micro-Expression Recognition Based on Spatio-Temporal Feature Extraction of Key Regions
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作者 Wenqiu Zhu Yongsheng Li +1 位作者 Qiang Liu Zhigao Zeng 《Computers, Materials & Continua》 SCIE EI 2023年第10期1373-1392,共20页
Aiming at the problems of short duration,low intensity,and difficult detection of micro-expressions(MEs),the global and local features of ME video frames are extracted by combining spatial feature extraction and tempo... Aiming at the problems of short duration,low intensity,and difficult detection of micro-expressions(MEs),the global and local features of ME video frames are extracted by combining spatial feature extraction and temporal feature extraction.Based on traditional convolution neural network(CNN)and long short-term memory(LSTM),a recognition method combining global identification attention network(GIA),block identification attention network(BIA)and bi-directional long short-term memory(Bi-LSTM)is proposed.In the BIA,the ME video frame will be cropped,and the training will be carried out by cropping into 24 identification blocks(IBs),10 IBs and uncropped IBs.To alleviate the overfitting problem in training,we first extract the basic features of the preprocessed sequence through the transfer learning layer,and then extract the global and local spatial features of the output data through the GIA layer and the BIA layer,respectively.In the BIA layer,the input data will be cropped into local feature vectors with attention weights to extract the local features of the ME frames;in the GIA layer,the global features of the ME frames will be extracted.Finally,after fusing the global and local feature vectors,the ME time-series information is extracted by Bi-LSTM.The experimental results show that using IBs can significantly improve the model’s ability to extract subtle facial features,and the model works best when 10 IBs are used. 展开更多
关键词 micro-expression recognition attention mechanism long and short-term memory network transfer learning identification block
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Micro-expression recognition algorithm based on graph convolutional network and Transformer model
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作者 吴进 PANG Wenting +1 位作者 WANG Lei ZHAO Bo 《High Technology Letters》 EI CAS 2023年第2期213-222,共10页
Micro-expressions are spontaneous, unconscious movements that reveal true emotions.Accurate facial movement information and network training learning methods are crucial for micro-expression recognition.However, most ... Micro-expressions are spontaneous, unconscious movements that reveal true emotions.Accurate facial movement information and network training learning methods are crucial for micro-expression recognition.However, most existing micro-expression recognition technologies so far focus on modeling the single category of micro-expression images and neural network structure.Aiming at the problems of low recognition rate and weak model generalization ability in micro-expression recognition, a micro-expression recognition algorithm is proposed based on graph convolution network(GCN) and Transformer model.Firstly, action unit(AU) feature detection is extracted and facial muscle nodes in the neighborhood are divided into three subsets for recognition.Then, graph convolution layer is used to find the layout of dependencies between AU nodes of micro-expression classification.Finally, multiple attentional features of each facial action are enriched with Transformer model to include more sequence information before calculating the overall correlation of each region.The proposed method is validated in CASME II and CAS(ME)^2 datasets, and the recognition rate reached 69.85%. 展开更多
关键词 micro-expression recognition graph convolutional network(GCN) action unit(AU)detection Transformer model
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Adaptive spatio-temporal attention neural network for cross-database micro-expression recognition
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作者 Yuhan RAN 《Virtual Reality & Intelligent Hardware》 2023年第2期142-156,共15页
Background The use of micro-expression recognition to recognize human emotions is one of the most critical challenges in human-computer interaction applications. In recent years, cross-database micro-expression recogn... Background The use of micro-expression recognition to recognize human emotions is one of the most critical challenges in human-computer interaction applications. In recent years, cross-database micro-expression recognition(CDMER) has emerged as a significant challenge in micro-expression recognition and analysis. Because the training and testing data in CDMER come from different micro-expression databases, CDMER is more challenging than conventional micro-expression recognition. Methods In this paper, an adaptive spatio-temporal attention neural network(ASTANN) using an attention mechanism is presented to address this challenge. To this end, the micro-expression databases SMIC and CASME II are first preprocessed using an optical flow approach,which extracts motion information among video frames that represent discriminative features of micro-expression.After preprocessing, a novel adaptive framework with a spatiotemporal attention module was designed to assign spatial and temporal weights to enhance the most discriminative features. The deep neural network then extracts the cross-domain feature, in which the second-order statistics of the sample features in the source domain are aligned with those in the target domain by minimizing the correlation alignment(CORAL) loss such that the source and target databases share similar distributions. Results To evaluate the performance of ASTANN, experiments were conducted based on the SMIC and CASME II databases under the standard experimental evaluation protocol of CDMER. The experimental results demonstrate that ASTANN outperformed other methods in relevant crossdatabase tasks. Conclusions Extensive experiments were conducted on benchmark tasks, and the results show that ASTANN has superior performance compared with other approaches. This demonstrates the superiority of our method in solving the CDMER problem. 展开更多
关键词 Cross-database micro-expression recognition Deep learning Attention mechanism Domain adaption
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Review of micro-expression spotting and recognition in video sequences 被引量:2
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作者 Hang PAN Lun XIE +3 位作者 Zhiliang WANG Bin LIU Minghao YANG Jianhua TAO 《Virtual Reality & Intelligent Hardware》 2021年第1期1-17,共17页
Facial micro-expressions are short and imperceptible expressions that involuntarily reveal the true emotions that a person may be attempting to suppress,hide,disguise,or conceal.Such expressions can reflect a person&#... Facial micro-expressions are short and imperceptible expressions that involuntarily reveal the true emotions that a person may be attempting to suppress,hide,disguise,or conceal.Such expressions can reflect a person's real emotions and have a wide range of application in public safety and clinical diagnosis.The analysis of facial micro-expressions in video sequences through computer vision is still relatively recent.In this research,a comprehensive review on the topic of spotting and recognition used in micro expression analysis databases and methods,is conducted,and advanced technologies in this area are summarized.In addition,we discuss challenges that remain unresolved alongside future work to be completed in the field of micro-expression analysis. 展开更多
关键词 Facial expression micro-expression spotting micro-expression recognition DATABASE REVIEW
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Gender-Specific Multi-Task Micro-Expression Recognition Using Pyramid CGBP-TOP Feature
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作者 Chunlong Hu Jianjun Chen +3 位作者 Xin Zuo Haitao Zou Xing Deng Yucheng Shu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2019年第3期547-559,共13页
Micro-expression recognition has attracted growing research interests in the field of compute vision.However,micro-expression usually lasts a few seconds,thus it is difficult to detect.This paper presents a new framew... Micro-expression recognition has attracted growing research interests in the field of compute vision.However,micro-expression usually lasts a few seconds,thus it is difficult to detect.This paper presents a new framework to recognize micro-expression using pyramid histogram of Centralized Gabor Binary Pattern from Three Orthogonal Panels(CGBP-TOP)which is an extension of Local Gabor Binary Pattern from Three Orthogonal Panels feature.CGBP-TOP performs spatial and temporal analysis to capture the local facial characteristics of micro-expression image sequences.In order to keep more local information of the face,CGBP-TOP is extracted based on pyramid subregions of the micro-expression video frame.The combination of CGBP-TOP and spatial pyramid can represent well and truly the facial movements of the micro-expression image sequences.However,the dimension of our pyramid CGBP-TOP tends to be very high,which may lead to high data redundancy problem.In addition,it is clear that people of different genders usually have different ways of micro-expression.Therefore,in this paper,in order to select the relevant features of micro-expression,the gender-specific sparse multi-task learning method with adaptive regularization term is adopted to learn a compact subset of pyramid CGBP-TOP feature for micro-expression classification of different sexes.Finally,extensive experiments on widely used CASME II and SMIC databases demonstrate that our method can efficiently extract micro-expression motion features in the micro-expression video clip.Moreover,our proposed approach achieves comparable results with the state-of-the-art methods. 展开更多
关键词 micro-expression recognition FEATURE extraction spatial PYRAMID MULTI-TASK learning REGULARIZATION
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Micro-expression recognition algorithm based on the combination of spatial and temporal domains
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作者 Wu Jin Xi Meng +2 位作者 Dai Wei Wang Lei Wang Xinran 《High Technology Letters》 EI CAS 2021年第3期303-309,共7页
Aiming at the problem of unsatisfactory effects of traditional micro-expression recognition algorithms,an efficient micro-expression recognition algorithm is proposed,which uses convolutional neural networks(CNN)to ex... Aiming at the problem of unsatisfactory effects of traditional micro-expression recognition algorithms,an efficient micro-expression recognition algorithm is proposed,which uses convolutional neural networks(CNN)to extract spatial features of micro-expressions,and long short-term memory network(LSTM)to extract time domain features.CNN and LSTM are combined as the basis of micro-expression recognition.In many CNN structures,the visual geometry group(VGG)using a small convolution kernel is finally selected as the pre-network through comparison.Due to the difficulty of deep learning training and over-fitting,the dropout method and batch normalization method are used to solve the problem in the VGG network.Two data sets CASME and CASME II are used for test comparison,in order to solve the problem of insufficient data sets,randomly determine the starting frame,and a fixedlength frame sequence is used as the standard,and repeatedly read all sample frames of the entire data set to achieve trayersal and data amplification.Finallv.a hieh recognition rate of 67.48% is achieved. 展开更多
关键词 micro-expression recognition convolutional neural network(CNN) long short-term memory(LSTM) batch normalization algorithm DROPOUT
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An improved micro-expression recognition algorithm of 3D convolutional neural network
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作者 WU Jin SHI Qianwen +2 位作者 XI Meng WANG Lei ZENG Huadie 《High Technology Letters》 EI CAS 2022年第1期63-71,共9页
The micro-expression lasts for a very short time and the intensity is very subtle.Aiming at the problem of its low recognition rate,this paper proposes a new micro-expression recognition algorithm based on a three-dim... The micro-expression lasts for a very short time and the intensity is very subtle.Aiming at the problem of its low recognition rate,this paper proposes a new micro-expression recognition algorithm based on a three-dimensional convolutional neural network(3D-CNN),which can extract two-di-mensional features in spatial domain and one-dimensional features in time domain,simultaneously.The network structure design is based on the deep learning framework Keras,and the discarding method and batch normalization(BN)algorithm are effectively combined with three-dimensional vis-ual geometry group block(3D-VGG-Block)to reduce the risk of overfitting while improving training speed.Aiming at the problem of the lack of samples in the data set,two methods of image flipping and small amplitude flipping are used for data amplification.Finally,the recognition rate on the data set is as high as 69.11%.Compared with the current international average micro-expression recog-nition rate of about 67%,the proposed algorithm has obvious advantages in recognition rate. 展开更多
关键词 micro-expression recognition deep learning three-dimensional convolutional neural network(3D-CNN) batch normalization(BN)algorithm DROPOUT
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An Automated and Real-time Approach of Depression Detection from Facial Micro-expressions 被引量:2
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作者 Ghulam Gilanie Mahmood ul Hassan +5 位作者 Mutyyba Asghar Ali Mustafa Qamar Hafeez Ullah Rehan Ullah Khan Nida Aslam Irfan Ullah Khan 《Computers, Materials & Continua》 SCIE EI 2022年第11期2513-2528,共16页
Depression is a mental psychological disorder that may cause a physical disorder or lead to death.It is highly impactful on the socialeconomical life of a person;therefore,its effective and timely detection is needful... Depression is a mental psychological disorder that may cause a physical disorder or lead to death.It is highly impactful on the socialeconomical life of a person;therefore,its effective and timely detection is needful.Despite speech and gait,facial expressions have valuable clues to depression.This study proposes a depression detection system based on facial expression analysis.Facial features have been used for depression detection using Support Vector Machine(SVM)and Convolutional Neural Network(CNN).We extracted micro-expressions using Facial Action Coding System(FACS)as Action Units(AUs)correlated with the sad,disgust,and contempt features for depression detection.A CNN-based model is also proposed in this study to auto classify depressed subjects from images or videos in real-time.Experiments have been performed on the dataset obtained from Bahawal Victoria Hospital,Bahawalpur,Pakistan,as per the patient health questionnaire depression scale(PHQ-8);for inferring the mental condition of a patient.The experiments revealed 99.9%validation accuracy on the proposed CNN model,while extracted features obtained 100%accuracy on SVM.Moreover,the results proved the superiority of the reported approach over state-of-the-art methods. 展开更多
关键词 Depression detection facial micro-expressions facial landmarked images
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Michel Serres and the Posthumanism: Silencing, Recognizing, and Working on Absences 被引量:1
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作者 Orsola Rignani 《Journal of Philosophy Study》 2022年第3期167-171,共5页
Faced with a socio-political-mediatic arena that continues to return the ballet of pandemic,climate change,fourth industrial revolution,sixth mass extinction,war etc.,the reflection of Michel Serres and Posthumanism p... Faced with a socio-political-mediatic arena that continues to return the ballet of pandemic,climate change,fourth industrial revolution,sixth mass extinction,war etc.,the reflection of Michel Serres and Posthumanism put forth instances for silencing of the anthropocentric logos,and for recognition of the multiplicity,variety,possibility of things and of the human in co-belonging with them,as well as instances for working on these same multiplicities,varieties,possibilities,that are often absences,black holes,repressed of philosophical thought. 展开更多
关键词 Michel Serres POSTHUMANISM SILENCING recognizing ABSENCES
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Spatial information recognizing of ocean eddies based on virtual force field and its application
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作者 LI Ce DU Yunyan SU Fenzhen YANG Xiaomei XU Jun 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2007年第4期44-52,共9页
A new approach to detecting ocean eddies automatically from remote sensing imageries based on the ocean eddy's eigen-pattern in remote sensing imagery and "force field-based shape extracting method" is proposed. Fi... A new approach to detecting ocean eddies automatically from remote sensing imageries based on the ocean eddy's eigen-pattern in remote sensing imagery and "force field-based shape extracting method" is proposed. First, the analysis on extracting eddies' edges from remote sensing imagery using conventional edge detection arithmetic operators is performed and returns digitized vector edge data as a result. Second, attraction forces and fusion forces between edge curves were analyzed and calculated based on the vector eddy edges. Thirdly, the virtual significant spatial patterns of eddy were detected automatically using iterative repetition followed by optimized rule. Finally, the spatial form auto-detection of different types of ocean eddies was done using satellite images. The study verified that this is an effective way to identify and detect the ocean eddy with a complex form. 展开更多
关键词 ocean eddy spatial pattern recognizing force field detection
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Research of recognizing intelligence based on commanding decision-making
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作者 Liu Jingxue Fei Qi 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2006年第4期775-780,共6页
In commanding decision-making, the commander usually needs to know a lot of situations(intelligence) on the adversary. Because of the military intelligence with opposability, it is inevitable that intelligence perso... In commanding decision-making, the commander usually needs to know a lot of situations(intelligence) on the adversary. Because of the military intelligence with opposability, it is inevitable that intelligence personnel take some deceptive information released by the rival as intelligence data in the process of intelligence gathering. Since the failure of intelligence is likely to lead to a serious aftereffect, the recognition of intelligence is a very important problem. An elementary research on recognizing military intelligence and puts forward a systematic processing method are made. First, the types and characteristics of military intelligence are briefly discussed, a research thought of recognizing military intelligence by means of recognizing military hypotheses are presented. Next, the reasoning mode and framework for recognizing military hypotheses are presented from the angle of psychology of intelligence analysis and non-monotonic reasoning. Then, a model for recognizing military hypothesis is built on the basis of fuzzy judgement information given by intelligence analysts. A calculative example shows that the model has the characteristics of simple calculation and good maneuverability. Last, the methods that selecting the most likely hypothesis from the survival hypotheses via final recognition are discussed. 展开更多
关键词 psychology of intelligence analysis non-monotonic reasoning fuzzy judgement recognizing model D-S theory LOWA operator.
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Recognizing Africa
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作者 Chika Ezeanya-Esiobu 《ChinAfrica》 2017年第2期36-36,共1页
THE 2017 WorldEconomic Forum (WEF) held in Davos in January placed a spotlight on the increasing dissatisfaction and disgruntlement that characterize the mindset of a growing number of global citizens, cutting acros... THE 2017 WorldEconomic Forum (WEF) held in Davos in January placed a spotlight on the increasing dissatisfaction and disgruntlement that characterize the mindset of a growing number of global citizens, cutting across nationalities and continents. Themed "Responsive and Responsible Leadership," organizers sought to use the platform to congregate ideas, 展开更多
关键词 WEF recognizing Africa
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Cognitive-affective regulation process for micro-expressions based on Gaussian cloud distribution
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作者 Xiujun Yang Lun Xie +1 位作者 Jing Han Zhiliang Wang 《CAAI Transactions on Intelligence Technology》 2017年第1期56-61,共6页
In this paper, we explore the process of emotional state transition. And the process is impacted by emotional state of interaction objects. First of all, the cognitive reasoning process and the micro-expressions recog... In this paper, we explore the process of emotional state transition. And the process is impacted by emotional state of interaction objects. First of all, the cognitive reasoning process and the micro-expressions recognition is the basis of affective computing adjustment process. Secondly, the threshold function and attenuation function are proposed to quantify the emotional changes. In the actual environment, the emotional state of the robot and external stimulus are also quantified as the transferring probability. Finally, the Gaussian cloud distribution is introduced to the Gross model to calculate the emotional transitional probabilities. The experimental results show that the model in human-computer interaction can effectively regulate the emotional states, and can significantly improve the humanoid and intelligent ability of the robot. This model is consistent with experimental and emulational significance of the psychology, and allows the robot to get rid of the mechanical emotional transfer process. 展开更多
关键词 micro-expression Cognitive-affective regulation Gaussian cloud distribution Transferring probability Emotional intensity
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分配·承认·能力:职业教育高考制度正义的多维审视
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作者 杨磊 朱德全 《内蒙古社会科学》 北大核心 2024年第2期187-197,共11页
职业教育高考制度正义是揭示其作为一项“好制度”的根本所在,旨在彰显职业教育类型化变革和职业教育人才选拔的时代精神。职业教育高考制度正义指高等职业院校入学招生考试制度的正义属性,既包含职业教育高考制度中的正义追求,也包含... 职业教育高考制度正义是揭示其作为一项“好制度”的根本所在,旨在彰显职业教育类型化变革和职业教育人才选拔的时代精神。职业教育高考制度正义指高等职业院校入学招生考试制度的正义属性,既包含职业教育高考制度中的正义追求,也包含职业教育高考制度内容的正义以及制度执行手段的正义,还包含职业教育高考制度所形成的高考文化、高考风俗、高考习惯以及高考心理、高考舆论等制度亚文化的正义性。职业教育高考制度正义还是多元化、层次化的复合正义,具体包含优质教育资源的分配正义、教育主体地位的承认正义、个体自由发展的能力正义。是故,职业教育高考制度在制定与执行中需要强调权利的平等、机会的公平、民主的平等,以教育考试制度的正义性变革实现人的自由发展。 展开更多
关键词 职教高考 制度正义 分配正义 承认正义 能力正义
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中国老年髋部及椎体骨折大数据分析报告
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作者 宋纯理 《中华骨质疏松和骨矿盐疾病杂志》 CSCD 北大核心 2024年第4期303-307,共5页
骨质疏松及骨质疏松性骨折是一个全球性公共卫生问题,具有发病率高、致死致残率高、社会医疗负担重的特点。然而,全国性的骨质疏松性骨折的流行病学数据不足。我们利用中国城镇职工基础医疗保险(Urban Employee Basic Medical Insurance... 骨质疏松及骨质疏松性骨折是一个全球性公共卫生问题,具有发病率高、致死致残率高、社会医疗负担重的特点。然而,全国性的骨质疏松性骨折的流行病学数据不足。我们利用中国城镇职工基础医疗保险(Urban Employee Basic Medical Insurance,UEBMI)和城镇居民基础医疗保险(Urban Resident Basic Medical Insurance,URBMI)数据库对55岁(椎体骨折为50岁)及以上老年人群的髋部/椎体骨折进行了分析,并计算其发生率和医疗费用。研究共纳入190560例髋部骨折(女性121933例,男性68509例,平均年龄77.05岁)和271981例椎体骨折(女性186428例,男性85553例平均年龄70.26岁)。中国55岁及以上老年人群的髋部骨折发生率从2012年的148.75/10万缓慢下降到2016年的136.65/10万。中国50岁及以上老年人群的椎体骨折发生率从2013年的85.21/10万增加到2017年的152.13/10万。髋部骨折住院总费用五年间增长约4倍;椎体骨折的医疗费用则增长了5.45倍;无论髋部骨折还是椎体骨折,人均治疗费用稳步降低。中国城镇老年人群髋部骨折发生率达到了一个平台期,但椎体骨折发病率呈上升态势。与此同时,髋部骨折和椎体骨折的总人数和总相关医疗花费仍然在迅速增长。研究结果提示我们应更加重视骨质疏松症的管理和骨质疏松骨折的防控。 展开更多
关键词 骨质疏松 流行病学 髋部骨折 椎体骨折 医疗花费
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基于邻域粗集神经网络的大数据特征分类系统
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作者 朱磊 凌嘉敏 《电子设计工程》 2024年第7期97-100,105,共5页
为提升主机元件对大数据的分类准确性,尽可能地避免数据误传,提出基于邻域粗集神经网络的大数据特征分类系统。在邻域粗集神经网络中,完成对邻域系数的粒化处理,通过逼近运算的方式,使神经网络模型快速趋于稳定。选取大数据特征调制信息... 为提升主机元件对大数据的分类准确性,尽可能地避免数据误传,提出基于邻域粗集神经网络的大数据特征分类系统。在邻域粗集神经网络中,完成对邻域系数的粒化处理,通过逼近运算的方式,使神经网络模型快速趋于稳定。选取大数据特征调制信息,借助调制识别器元件控制大数据特征的导出方向,结合关联信道组织完成数据特征的多标合并处理。实验表明,利用该系统可将大数据的单位召回率提升至65%,能够促进主机元件对大数据的准确分类。 展开更多
关键词 邻域粗集 神经网络 大数据特征 粒化处理 调制识别器 多标合并
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欧盟河流地貌单元调查和分类系统(GUS)的浅析与启示
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作者 王宏涛 冯硕 +4 位作者 刘佳利 张晶 赵进勇 王琦 刘一璇 《环境生态学》 2024年第10期10-18,共9页
河流地貌形态是自然栖息地评估的关键,河流地貌单元调查和评估对河流生态系统保护与修复具有重要作用。为了更好地识别多样的地貌单元类型,评估河道的复杂性和栖息地潜力,通过从多层次地貌单元分类框架、多水平地貌单元调查技术体系和... 河流地貌形态是自然栖息地评估的关键,河流地貌单元调查和评估对河流生态系统保护与修复具有重要作用。为了更好地识别多样的地貌单元类型,评估河道的复杂性和栖息地潜力,通过从多层次地貌单元分类框架、多水平地貌单元调查技术体系和地貌单元多样性评估3个方面梳理欧盟提出的河流地貌单元调查和分类系统(GUS)成果,并提出GUS系统在我国河流地貌调查方面的适用性,以赤水河流域鱼洞河为GUS系统应用案例,对鱼洞河地貌单元进行分类识别。GUS对我国的河流生物栖息地修复与综合管理有很好的指导和借鉴意义。 展开更多
关键词 河流地貌单元 分类 识别 栖息地 生态响应
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面部皮肤分型方法的研究进展
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作者 陈子暄 张铮 章一新 《组织工程与重建外科》 CAS 2024年第3期378-381,共4页
皮肤分型是用于描述皮肤特征的常用手段。传统的皮肤分型(如Fitzpatrick皮肤光型、Baumann皮肤分型等)各有其优缺点,但都通过主观判断来评价皮肤类型,缺乏皮肤客观参数的定量分析。近年来,皮脂分泌量、经皮水丢失等客观参数的测量技术... 皮肤分型是用于描述皮肤特征的常用手段。传统的皮肤分型(如Fitzpatrick皮肤光型、Baumann皮肤分型等)各有其优缺点,但都通过主观判断来评价皮肤类型,缺乏皮肤客观参数的定量分析。近年来,皮脂分泌量、经皮水丢失等客观参数的测量技术取得了较大发展,使得客观参数描述皮肤类型成为可能。此外,基于面部照片的图像识别技术能提取面部皮肤特征,为皮肤分型提供依据。本文就主观皮肤分型方法、皮肤客观参数检测,以及基于图像识别的皮肤分析技术等进行综述,探讨皮肤分型从定性-定量-可视化的发展过程,以期为今后对皮肤进行客观、精细的分型提供理论依据。 展开更多
关键词 皮肤分型 客观参数 图像识别
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伽马-伽马测井在鄂尔多斯盆地西南缘白垩系识别岩性的研究
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作者 王伟 武正乾 +7 位作者 贺锋 刘坤鹏 王晓鹏 李磊 喻腾 毛宁 张良 李西得 《世界核地质科学》 CAS 2024年第2期343-350,共8页
近年来鄂尔多斯盆地西南缘白垩系砂岩型铀矿找矿取得突破,由于研究区白垩系特殊的沉积环境,环河组的泥岩和粉砂岩中广泛发育石膏类不导电矿物,导致常规测井曲线难以准确解释岩性。为了准确区分非渗透(泥岩、粉砂岩)和渗透砂岩,经过测量... 近年来鄂尔多斯盆地西南缘白垩系砂岩型铀矿找矿取得突破,由于研究区白垩系特殊的沉积环境,环河组的泥岩和粉砂岩中广泛发育石膏类不导电矿物,导致常规测井曲线难以准确解释岩性。为了准确区分非渗透(泥岩、粉砂岩)和渗透砂岩,经过测量研究区岩石物性参数,发现泥岩、粉砂岩类岩石密度大于砂岩密度,伽马—伽马测井广泛应用在砂岩型铀矿地球物理测井工作中,用来计算地层密度,长、短源距测井参数为其中间测量参数,为了更好地发挥其作用,阐明了伽马-伽马测井原理,结合自然伽马与长、短源距拟合关系,优选了抗干扰强的短源距测井曲线,提出了自然伽马曲线消除长、短源距消除放射性矿层影响的校正方法。经钻孔岩性和测井曲线验证,伽马-伽马测井的短源距曲线可以较好地解释研究区白垩系岩性,对鄂尔多斯盆地西南缘白垩系砂岩型铀矿地球物理测井工作具有一定参考意义。 展开更多
关键词 伽马-伽马测井 鄂尔多斯盆地 白垩系 识别岩性
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浅析傅仁宇之《审视瑶函·识病辨症详明金玉赋》
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作者 朱佳美 周剑 +2 位作者 闫晓玲 唐梦丹 祁宝玉 《中国中医眼科杂志》 2024年第6期539-541,557,共4页
明末眼科名家傅仁宇所作的《审视瑶函•识病辨症详明金玉赋》是中医眼科诊法名篇,文中警句至今为各类教材及著作沿用。本文按照胞睑、两眦、白睛等病位及视觉、目红、目痛等眼部症状对相关警句进行分类整理,以便读者查阅背诵。并结合现... 明末眼科名家傅仁宇所作的《审视瑶函•识病辨症详明金玉赋》是中医眼科诊法名篇,文中警句至今为各类教材及著作沿用。本文按照胞睑、两眦、白睛等病位及视觉、目红、目痛等眼部症状对相关警句进行分类整理,以便读者查阅背诵。并结合现代疾病认识及病证结合模式客观评述其病名不妥、病与病机不符、内容排列混杂等瑕疵。虽有不足,其歌赋体裁及病症要点为古今眼科初学者提供了宝贵的资料。 展开更多
关键词 傅仁宇 审视瑶函 识病辨症
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