Paired regions for shadow removal approach based on multi-features

The existence of shadow leads to the degradation of the image qualities and the defect of ground object information.Shadow removal is therefore an essential research topic in image processing filed.The biggest challenge of shadow removal is how to restore the content of shadow areas correctly while removing the shadow in the image.Paired regions for shadow removal approach based on multi-features is proposed, in which shadow removal is only performed on related sunlit areas.Feature distance between regions is calculated to find the optimal paired regions with considering of multi-features(texture, gradient feature, etc.) comprehensively.Images in different scenes with peak signal-to-noise ratio(PSNR) and structural similarity(SSIM) evaluation indexes are chosen for experiments.The results are shown with six existing comparison methods by visual and quantitative assessments, which verified that the proposed method shows excellent shadow removal effect, the brightness, color of the removed shadow area, and the surrounding non-shadow area can be naturally fused.

MVCE-Net: Multi-View Region Feature and Caption Enhancement Co-Attention Network for Visual Question Answering

Visual question answering(VQA)requires a deep understanding of images and their corresponding textual questions to answer questions about images more accurately.However,existing models tend to ignore the implicit knowledge in the images and focus only on the visual information in the images,which limits the understanding depth of the image content.The images contain more than just visual objects,some images contain textual information about the scene,and slightly more complex images contain relationships between individual visual objects.Firstly,this paper proposes a model using image description for feature enhancement.This model encodes images and their descriptions separately based on the question-guided coattention mechanism.This mechanism increases the feature representation of the model,enhancing the model’s ability for reasoning.In addition,this paper improves the bottom-up attention model by obtaining two image region features.After obtaining the two visual features and the spatial position information corresponding to each feature,concatenating the two features as the final image feature can better represent an image.Finally,the obtained spatial position information is processed to enable the model to perceive the size and relative position of each object in the image.Our best single model delivers a 74.16%overall accuracy on the VQA 2.0 dataset,our model even outperforms some multi-modal pre-training models with fewer images and a shorter time.

Grid Side Distributed Energy Storage Cloud Group End Region Hierarchical Time-Sharing Configuration Algorithm Based onMulti-Scale and Multi Feature Convolution Neural Network

There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

Individual alcohol consumption by the population of Russia versus regional living conditions

Background:There are substantial regional differences in drinking alcohol in Russia,both at the population and individual levels.However,the causes of these differences have not been studied yet.Objective:The goal of our study was to examine the effect of regional living conditions on individual alcohol consumption by the population of Russia.Methods:For the analysis,we used data from a cross-sectional epidemiological study conducted in 2013-2014.The final analytical sample included 18,130 people aged 25-64 years.We conducted the interviews face to face,based on which any drinking in the last year,as well as alcohol abuse,were considered as a response.Alcohol abuse was recorded when the respondent consumed 5.75 or more grams of pure ethanol per day(75th percentile of average daily alcohol consumption among alcohol drinkers).The assessment of the regional living conditions was accomplished via integral indexing,which was previously performed based on publicly available data for 2010-2014.Associations were assessed using generalized scoring equations with unchanging standard errors.The associations were expressed by odds ratios(OR)and 95%confidence intervals(C).Results:Deterioration of social conditions and increase in demographic depression in the region of residence increased the odds of any drinking(OR 1.51,95%CI:1.33 to 1.72,P<0.001 and OR 1.22,95%CI:1.05 to 1.41,P=0.oo9,respectively).The odds of alcohol abuse increased with the deterioration of social living conditions and the growth of the industrial development in the region:OR 1.35,95%CI:1.14 to 1.59,P<0.001 and OR 1.16,95%CI:1.05 to 1.28,P=0.002,respectively.Conclusion:Our analysis allowed assessing the impact of the regional living conditions on individual drinking alcohol in the population of Russia.

Park Planning and Design Integrated with Regional Features

Natural environment and historical humanities are the two elements constituting regional features.The construction of urban park should search design language from regional features.The author,taking Dongshan Park in Qianxi County,Hebei Province as an example,discussed how to search local natural environment features,reasonably exploit cultural resources and integrate regional features from the establishment of planning theme to the expression of designing details.

Studies on the regional feature of organic carbon in sediments off the Huanghe River Estuary waters

Organic carbon (OC) in definitely small area sediments(according to marine dimension)off the Huanghe River Estuary is investigated in order to evaluate the feature of regional difference of physical and chemical properties in marginal sea sediments.The distributions of OC in sediments with natural grain size and the relationship with the pH,Eh ,Es and Fe3+/Fe2+ are discussed.In addition,OC decomposition rates in surfacial/subsurfacial sediments are estimated.OC concentrations range from 0.26% to 1.8%(wt)in the study area. Significant differences in OC content and in horizontal distribution as well as various trends in surfacial /subsurfacial sediments exhibit the feature of regional difference remarkably in marginal sea sediments. The complicated distribution of OC in surface sediments is due to the influence of bacterial activity and abundance, bioturbation of benthos and physical disturbance. The OC decomposition rate constant in surfacial /subsurfacial sediments ranges from 0.009 7 to 0.076 a-1 and the relatively high values may be mainly related to bacteria that are mainly responsible for OC mineralization;meio-and macrofauna affect OC degradation both directly, through feeding on it, and indirectly through bioturbation and at the same time coarse sediments are also disadvantageous to OC preservation.In almost all the middle and bottom sediments the contents of OC decrease with the increase of deposition depth, which indicates that mineralization of OC in the middle and bottom sediments has occurred via processes like SO reduction and Fe-oxide reduction.

Evolution Rules and Spatial Features of Traditional Settlements in Fukou Xing Region

As one of the eight Taihang passes,Fukou Xing is located in the south of the Taihang Mountains and has been an important passage for Shanxi and Hebei in history.Taking traditional settlements in Fukou Xing Region as research object,using the Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER) Global Digital Elevation Model(GDEM)(remote sensing measurement of elevation data) and GIS platform,this paper made a quantitative study on traditional settlement space in mountain environment of this region,and studied space parameters including elevation,terrain,aspect,and boundary,observed and summarized the spatial features.In addition,based on the local chronicles of Ming and Qing dynasties,it mutually verified the quantitative conclusions and qualitative cognition,analyzed the evolution rules of traditional settlements in Fukou Xing region,and finally obtained new understandings of spatial features of traditional settlements in Fukou Xing region.

Regional Evolution Features and Coordinated Development Strategies for Northeast China

Northeast China, as the most important production base of agriculture, forestry, and livestock-breeding as well as the old industrial base in the whole country, has been playin a key role in the construction and development of China＇s economy. However, after the policy of reform and open-up was taken in China. the economic development speed and efficiency ofthis area have turned to be evidently lower than those of coastal area and the national average level as well, which is so-called ＇Northeast Phenomenon＇ and ＇Neo-Northeast Phenomenon＇. In terms of those phenomena, this paper firstly reviews the spatial and temporal features of the regional evolution of this area so as to unveil the profound forming causes of ＇Northeast Phenomena＇ and ＇Neo-Northeast Phenomena＇. And then the paper makes a further exploration into the status quo of this region and its forming causes by analyzing its economy gross, industrial structure, product structure, regional eco-categories, etc. At the end of the paper, the authors put forward the basic coordinated development strategies for Northeast China. namely we can revitalize this area by means of adjustment of economic structure, regional coordination, planning urban and rural areas as a whole, institutional innovation, etc.

REGIONAL FEATURES OF LONG-TERM SST VARIATION IN THE WESTERN PACIFIC WARM POOL AREA

The main features of SST interannual and long term variations in the Western Pacific Warm Pool area were studied by using regression analysis, running t test and spectral analysis methods based on monthly mean SST data in the Pacific during 1950-1998. The results showed that the SST inter annual and long term variations in the Western Pacific Warm Pool area had evident regional features. There were significant differences in variation range, phase, period, occurrence time of abrupt variation between SST in the eastern area (east of 160°E) and SST in the western area (west of 160°E).

A NOVEL REGION FEATURE USED IN MULTISENSOR IMAGE FUSION

A new region feature which emphasized the salience of target region and its neighbors is proposed. In region segmentation-based multisensor image fusion scheme, the presented feature can be extracted from each segmented region to determine the fusion weight. Experimental results demonstrate that the proposed feature has extensive application scope and it provides much more information for each region. It can not only be used in image fusion but also be used in other image processing applications.

Loci Features of Government Office Garden in Regional Context: A Case Study of Yanhuachi in Chengdu City, China

Yanhuachi (Pool of Colorful Paintings) in west Chengdu City is a representative of government office garden among west Sichuan gardens. Gardening features of Yanhuachi were analyzed from the perspectives of landscape layout, garden architecture, plant environment and garden theme, and loci features of government office garden demonstrated by Yanhuachi in the regional context of Xishu were refined and summarized. Design of Yanhuachi displayed that water was introduced to ancient Chinese government office gardens for landscaping. This study aimed at providing references for the future regional garden construction.

Geochemical Features of a Subduction Initiation Ophiolite Type in Habana-Matanzas Region(Western Cuba)

We present new geochemical data for the upper mantle and crustal sections(whole-rock major and trace element compositions)as well as mineral chemical data,from the Northern Carbibbean ophiolites in the Habana-Matanzas region in Western Cuba.These ophiolites are part of the Northern Cuban Ophiolitic Belt(NCOB),extending for more than 1000 km along the island.The upper mantle peridotites are composed mainly of refractory harzburgite with tectonite textures,and show convex-downward patterns depleted in MREE normalized to chondrite values(Mc Donough and Sun,1995).These geochemical trends are characteristic for depleted mantle wedge peridotites metasomatized by slab-derived,LREE enriched melts.The NCOB also includes abyssal peridotites having lower LREE/HREEratiosanddisplayingrelativelyhomogeneous and flat patterns from MREE to HREE.These peridotites represent fragments accreted into the continental margin from a subducted oceanic lithosphere.Gabbro and dolerite units in the NCOB are systematically depleted in High Field Strength Elements(HFSE:Nb,Ta,Hf,Ti)and REE with respect to N-MORB(<1 X N-MORB).Their melt evolution was affected by subduction input.Spatially associated granitic rocks have a volcanic arc geochemical affinity.Some mafic extrusive rocks within the NCOB exhibit boninitic signatures,and may represent the products of subduction initiation magmatism,whereas other extrusive rock occurrences display N-MORB to E-MORB geochemical fingerprints,slightly modified by subduction derived fluids.Using these geochemical data and constraints,we present a tectonomagmatic model for the evolution of the NCOB within the framework of the Caribbean geology.

Fine-Grained Features for Image Captioning

Image captioning involves two different major modalities(image and sentence)that convert a given image into a language that adheres to visual semantics.Almost all methods first extract image features to reduce the difficulty of visual semantic embedding and then use the caption model to generate fluent sentences.The Convolutional Neural Network(CNN)is often used to extract image features in image captioning,and the use of object detection networks to extract region features has achieved great success.However,the region features retrieved by this method are object-level and do not pay attention to fine-grained details because of the detection model’s limitation.We offer an approach to address this issue that more properly generates captions by fusing fine-grained features and region features.First,we extract fine-grained features using a panoramic segmentation algorithm.Second,we suggest two fusion methods and contrast their fusion outcomes.An X-linear Attention Network(X-LAN)serves as the foundation for both fusion methods.According to experimental findings on the COCO dataset,the two-branch fusion approach is superior.It is important to note that on the COCO Karpathy test split,CIDEr is increased up to 134.3%in comparison to the baseline,highlighting the potency and viability of our method.

Fusion of Region Extraction and Cross-Entropy SVM Models for Wheat Rust Diseases Classification

Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20%every year.The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques.The experienced evaluators take time to identify the disease which is highly laborious and too costly.If wheat rust diseases are predicted at the development stages,then fungicides are sprayed earlier which helps to increase wheat yield quality.To solve the experienced evaluator issues,a combined region extraction and cross-entropy support vector machine(CE-SVM)model is proposed for wheat rust disease identification.In the proposed system,a total of 2300 secondary source images were augmented through flipping,cropping,and rotation techniques.The augmented images are preprocessed by histogram equalization.As a result,preprocessed images have been applied to region extraction convolutional neural networks(RCNN);Fast-RCNN,Faster-RCNN,and Mask-RCNN models for wheat plant patch extraction.Different layers of region extraction models construct a feature vector that is later passed to the CE-SVM model.As a result,the Gaussian kernel function in CE-SVM achieves high F1-score(88.43%)and accuracy(93.60%)for wheat stripe rust disease classification.

基于改进随机Hough变换的圆形目标检测算法

圆形目标检测在各个领域得到了广泛应用.为了提高规则圆的检出效率、降低不规则圆的漏检率,文章提出了一种改进随机Hough变换的圆形目标检测算法.算法首先用区域增长和RGB二值分割等算法对不同背景的图像进行二值分割和去噪处理,接着对连通域分割的特征区域用具有圆形性特征的边缘点进行候选圆的检测和验证.实验对比结果表明,本文算法可以显著提高规则圆的检出效率、降低不规则圆的漏检率,算法计算量小、运行速度快、鲁棒性强.

基于改进Faster RCNN的微操作空间目标检测算法

将Faster RCNN引入微操作系统的目标检测之中。针对微操作空间下待检测目标存在尺度变化和在显微镜放大倍数较小时,待检测目标尺度过小、特征不明显的问题,提出了一种基于改进Faster RCNN的微操作空间目标检测算法。使用在图像分类任务中性能优越的深度残差网络提取图像的特征。引入递归特征金字塔网络,对特征进行融合。改进区域建议网络的采样策略,对损失函数进行优化。实验结果表明:这种改进的Faster RCNN算法能有效解决由于目标尺度变化和目标尺度过小带来的问题。相比通用的目标检测算法,该算法的准确度更高,速度更快,具有实际应用价值。

基于Transformer视觉特征融合的图像描述方法

现有图像描述方法只利用区域型视觉特征生成描述语句,忽略了网格型视觉特征的重要性,并且均为两阶段方法,从而影响了图像描述的质量。针对该问题,提出一种基于Transformer视觉特征融合的端到端图像描述方法。首先,在特征提取阶段,利用视觉特征提取器提取出区域型视觉特征和网格型视觉特征;其次,在特征融合阶段,通过视觉特征融合模块对区域型视觉特征和网格型视觉特征进行拼接;最后,将所有的视觉特征送入语言生成器中以生成图像描述。该方法各部分均基于Transformer模型实现,实现了一阶段方法。在MS-COCO数据集上的实验结果表明,所提方法能够充分利用区域型视觉特征与网格型视觉特征的优势,BLEU-1、BLEU-4、METEOR、ROUGE-L、CIDEr、SPICE指标分别达到83.1%、41.5%、30.2%、60.1%、140.3%、23.9%,优于目前主流的图像描述方法,能够生成更加准确和丰富的描述语句。