recognition

摘要： The Earth observation remote sensing images can display ground activities and status intuitively,which plays an important role in civil and military fields.However,the information obtained from the research only from the perspective of images is limited,so in this paper we conduct research from the perspective of video.At present,the main problems faced when using a computer to identify remote sensing images are:They are difficult to build a fixed regular model of the target due to their weak moving regularity.Additionally,the number of pixels occupied by the target is not enough for accurate detection.However,the number of moving targets is large at the same time.In this case,the main targets cannot be recognized completely.This paper studies from the perspective of Gestalt vision,transforms the problem ofmoving target detection into the problem of salient region probability,and forms a Saliency map algorithm to extract moving targets.On this basis,a convolutional neural network with global information is constructed to identify and label the target.And the experimental results show that the algorithm can extract moving targets and realize moving target recognition under many complex conditions such as target’s long-term stay and small-amplitude movement.

摘要： The International Olive Council(IOC) is an international intergovernmental organization dedicated to olive oil and table olives, aiming at modernizing olive production, coordinating olive policies, improving the regulation of international trade, defending the quality of the olive sector and promoting olive oil and table olives to increase their consumption. The IOC grants recognition of laboratories and tasting panels in annual trials when they meet the conditions given in the decisions adopting the IOC certificate for laboratories for the physico–chemical testing of olive oil and laboratories for the sensory analysis of virgin olive oils. The IOC establishes analysis methods applying to olive oils and olive pomace oils for purity, quality and organoleptic assessment. The IOC elaborates guides of storage conditions for olive oils and olive pomace oils, of managing virgin olive oil tasting panels and of sensory testing laboratories. In future works, the IOC includes activities to identify analytical criteria for detecting fraud and guaranteeing the quality of olive oils and olive pomace oils.

摘要： Image translation plays a significant role in realistic image synthesis,entertainment tasks such as editing and colorization,and security including personal identification.In Edge GAN,the major contribution is attribute guided vector that enables high visual quality content generation.This research study proposes automatic face image realism from freehand sketches based on Edge GAN.We propose a density variant image synthesis model,allowing the input sketch to encompass face features with minute details.The density level is projected into non-latent space,having a linear controlled function parameter.This assists the user to appropriately devise the variant densities of facial sketches and image synthesis.Composite data set of Large Scale CelebFaces Attributes(ClebA),Labelled Faces in theWild(LFWH),Chinese University of Hong Kong(CHUK),and self-generated Asian images are used to evaluate the proposed approach.The solution is validated to have the capability for generating realistic face images through quantitative and qualitative results and human evaluation.

摘要： This paper presents a handwritten document recognition system based on the convolutional neural network technique.In today’s world,handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users.This technology is also helpful for the automatic data entry system.In the proposed systemprepared a dataset of English language handwritten character images.The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents.In this research,multiple experiments get very worthy recognition results.The proposed systemwill first performimage pre-processing stages to prepare data for training using a convolutional neural network.After this processing,the input document is segmented using line,word and character segmentation.The proposed system get the accuracy during the character segmentation up to 86%.Then these segmented characters are sent to a convolutional neural network for their recognition.The recognition and segmentation technique proposed in this paper is providing the most acceptable accurate results on a given dataset.The proposed work approaches to the accuracy of the result during convolutional neural network training up to 93%,and for validation that accuracy slightly decreases with 90.42%.

摘要： Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer Vision.Computer vision is one of the most active research fields that lies at the intersection of deep learning and machine vision.This paper presents an efficient ensemble algorithm for the recognition and tracking of fixed shapemoving objects while accommodating the shift and scale invariances that the object may encounter.The first part uses the Maximum Average Correlation Height(MACH)filter for object recognition and determines the bounding box coordinates.In case the correlation based MACH filter fails,the algorithms switches to a much reliable but computationally complex feature based object recognition technique i.e.,affine scale invariant feature transform(ASIFT).ASIFT is used to accommodate object shift and scale object variations.ASIFT extracts certain features from the object of interest,providing invariance in up to six affine parameters,namely translation(two parameters),zoom,rotation and two camera axis orientations.However,in this paper,only the shift and scale invariances are used.The second part of the algorithm demonstrates the use of particle filters based Approximate Proximal Gradient(APG)technique to periodically update the coordinates of the object encapsulated in the bounding box.At the end,a comparison of the proposed algorithm with other stateof-the-art tracking algorithms has been presented,which demonstrates the effectiveness of the proposed algorithm with respect to the minimization of tracking errors.

摘要： Human Action Recognition(HAR)is a current research topic in the field of computer vision that is based on an important application known as video surveillance.Researchers in computer vision have introduced various intelligent methods based on deep learning and machine learning,but they still face many challenges such as similarity in various actions and redundant features.We proposed a framework for accurate human action recognition(HAR)based on deep learning and an improved features optimization algorithm in this paper.From deep learning feature extraction to feature classification,the proposed framework includes several critical steps.Before training fine-tuned deep learning models–MobileNet-V2 and Darknet53–the original video frames are normalized.For feature extraction,pre-trained deep models are used,which are fused using the canonical correlation approach.Following that,an improved particle swarm optimization(IPSO)-based algorithm is used to select the best features.Following that,the selected features were used to classify actions using various classifiers.The experimental process was performed on six publicly available datasets such as KTH,UT-Interaction,UCF Sports,Hollywood,IXMAS,and UCF YouTube,which attained an accuracy of 98.3%,98.9%,99.8%,99.6%,98.6%,and 100%,respectively.In comparison with existing techniques,it is observed that the proposed framework achieved improved accuracy.

摘要： Dignity is a key category in Marxist political philosophy.Marx criticized the realistic predicament caused by the materialization of human dignity in the capitalist society and indicated that the core of dignity lies in the manifestation and confirmation by means of labor,and time is one dimension for the measurement of labor.Hence,free time,lifetime,and emotional time are important paths and key characteristics to realize and safeguard dignity.The capitalist mode and relations of production cannot fundamentally realize human dignity.The realization of human dignity requires constructing a social system and public space and the full development of social conditions in all directions,for society is the fundamental way to realize and safeguard human dignity.Marx regarded the recognition of protecting dignity and worth for all people as the ultimate goal of realizing a life with dignity.Fully interpreting the concept of dignity in Marxism is of positive significance for building a better life.

摘要： Emotion recognition is to quantify,describe and recognize different emotional states through the behavioral and physiological responses generated from emotional expressions.Emotion recognition is an important field due to its wide applications in many tasks,such as dialogue generation,social media analysis and intelligent system.It builds a harmonious human-computer environment by enabling the computer systems and devices to recognize and interpret human affects.Emotion recognition models are built using multimodal information such as audio,video,text and so on.It is important to consider emotion characteristics of humans in the design and presentation of intelligent interaction.We have selected seven papers that provide the latest updates on the development of emotion recognition technology covering micro-expression spotting and recognition,speech emotion recognition,physiological signal emotion recognition,emotional dialog generation and so on.

摘要： Based on the proposal of freedom of speech,hate speech has become more and more widespread,especially in the past decade.Generally,the constituent elements of hate speech are mainly manifested in four aspects(Jiang,2015):the way of expression,the object,the intention of expression,and the harmful consequences.Through these four aspects,hate speech can give a heavy blow to the stability and security of the whole society with the help of social media.Hence,this paper puts forward an analysis method of the recognition and resistance to hate speech from different conditions.

摘要： The recognition mechanism of artificial intelligence(AI)is an interesting topic in understanding AI neural networks and their application in therapeutics.A number of multilayered neural networks can recognize cancer through deep learning.It would be interesting to think about whether human insights and AI attention are associated with each other or should be translated,which is one of the main points in this editorial.The automatic detection of cancer with computeraided diagnosis is being applied in the clinic and should be improved with feature mapping in neural networks.The subtypes and stages of cancer,in terms of progression and metastasis,should be classified with AI for optimized therapeutics.The determination of training and test data during learning and selection of appropriate AI models will be essential for therapeutic applications.

摘要： The article proposed a new way of facial expression recognition by reconstructing the PCAmethods. Separating the training set into 7 parts by expression, and get the Orthonormal Basis of each subsetexpression by PCA algorithm. Then make projection with the original image on each of the OrthonormalBasis, rebuilt the projection coordinate and recognize the expression by the combination of D-valuesummation and similarity methods. Finally, we get the final result by comparing the similarity between theoriginal and reconstruction image.

摘要： Because of having many advantages, diamond is applied widely in many fields. But the existenceof body defects will debase the application quality. A set of defect recognized system is established based onthe compensatory fuzzy neural network of using wavelet and with fast algorithm in this paper. The energy-defect method to extract eigenvalue is used firstly, then defect classification is recognized by fuzzy neuralnetwork. The results of simulation show that the model established by making use of this algorithm has higherefficiency, and the possibility of wrap in local minimum value of the network during the training process issmaller, which can compare to approach the precision utmost steadily and classification recognize the defectprecision. The experiment result can verify this system have very high accurate rate to forecast the bodydefects and satisfy the demand of the engineering application, which provide the technique guarantee forfurther realizing the diamond synthesis quantity monitor system.

摘要： Because of having many advantages, diamond is applied widely in many fields. But the existenceof body defects will debase the application quality. A set of defect recognized system is established based onthe compensatory fuzzy neural network of using wavelet and with fast algorithm in this paper. The energy-defect method to extract eigenvalue is used firstly, then defect classification is recognized by fuzzy neuralnetwork. The results of simulation show that the model established by making use of this algorithm has higherefficiency, and the possibility of wrap in local minimum value of the network during the training process issmaller, which can compare to approach the precision utmost steadily and classification recognize the defectprecision. The experiment result can verify this system have very high accurate rate to forecast the bodydefects and satisfy the demand of the engineering application, which provide the technique guarantee forfurther realizing the diamond synthesis quantity monitor system.

摘要： Because of having many advantages, diamond is applied widely in many fields. But the existenceof body defects will debase the application quality. A set of defect recognized system is established based onthe compensatory fuzzy neural network of using wavelet and with fast algorithm in this paper. The energy-defect method to extract eigenvalue is used firstly, then defect classification is recognized by fuzzy neuralnetwork. The results of simulation show that the model established by making use of this algorithm has higherefficiency, and the possibility of wrap in local minimum value of the network during the training process issmaller, which can compare to approach the precision utmost steadily and classification recognize the defectprecision. The experiment result can verify this system have very high accurate rate to forecast the bodydefects and satisfy the demand of the engineering application, which provide the technique guarantee forfurther realizing the diamond synthesis quantity monitor system.