The maximal guaranteed result in a hierarchical game with an undetermined factor is found in the class of strategies with feedback. The stability of the problem under consideration concerning perturbations of the payo...
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The paper considers the condition and comparison of representation on the Internet of both unaffected and reformed research institutions, in order to form a methodology for assessing the possibility of adequate and ti...
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Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compressio...
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Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.
Model quantification uses low bit-width values to represent the weight matrices of existing models to be quantized, which is a promising approach to reduce both storage and computational overheads of deploying highly ...
Autism Spectrum Disorder (ASD) refers to a neuro-disorder wherean individual has long-lasting effects on communication and interaction *** information technologywhich employs artificial intelligence(AI) model has assi...
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Autism Spectrum Disorder (ASD) refers to a neuro-disorder wherean individual has long-lasting effects on communication and interaction *** information technologywhich employs artificial intelligence(AI) model has assisted in early identify ASD by using pattern *** advances of AI models assist in the automated identification andclassification of ASD, which helps to reduce the severity of the *** study introduces an automated ASD classification using owl searchalgorithm with machine learning (ASDC-OSAML) model. The proposedASDC-OSAML model majorly focuses on the identification and classificationof ASD. To attain this, the presentedASDC-OSAML model follows minmaxnormalization approach as a pre-processing stage. Next, the owl searchalgorithm (OSA)-based feature selection (OSA-FS) model is used to derivefeature subsets. Then, beetle swarm antenna search (BSAS) algorithm withIterative Dichotomiser 3 (ID3) classification method was implied for ASDdetection and classification. The design of BSAS algorithm helps to determinethe parameter values of the ID3 classifier. The performance analysis of theASDC-OSAML model is performed using benchmark dataset. An extensivecomparison study highlighted the supremacy of the ASDC-OSAML modelover recent state of art approaches.
In repeated zero-sum games,instead of constantly playing an equilibrium strategy of the stage game,learning to exploit the opponent given historical interactions could typically obtain a higher ***,when playing agains...
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In repeated zero-sum games,instead of constantly playing an equilibrium strategy of the stage game,learning to exploit the opponent given historical interactions could typically obtain a higher ***,when playing against a fully adaptive opponent,one would have dificulty identifying the opponent's adaptive dynamics and further exploiting its potential *** this paper,we study the problem of optimizing against the adaptive opponent who uses no-regret ***-regret learning is a classic and widely-used branch of adaptive learning *** propose a general framework for online modeling no-regret opponents and exploiting their *** this framework,one could approximate the opponent's no-regret learning dynamics and then develop a response plan to obtain a significant profit based on the inferences of the opponent's *** employ two system identification architectures,including the recurrent neural network(RNN)and the nonlinear autoregressive exogenous model,and adopt an efficient greedy response plan within the ***,we prove the approximation capability of our RNN architecture at approximating specific no-regret ***,we demonstrate that during interactions at a low level of non-stationarity,our architectures could approximate the dynamics with a low error,and the derived policies could exploit the no-regret opponent to obtain a decent utility.
In document-level event extraction tasks, multiple event types often coexist within a document (the multi-event problem), and arguments may play different roles across different events (the argument intertwining probl...
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Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed ...
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Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed the development of medical image registration,they have not systematically summarized the existing med-ical image registration *** this end,a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives,aiming to help audiences quickly understand the development of medical image *** particular,we review recent advances in retinal image registration,which has not attracted much *** addition,current challenges in retinal image registration are discussed and insights and prospects for future research provided.
The problem of minimizing the maximum of N convex, Lipschitz functions plays significant roles in optimization and machine learning. It has a series of results, with the most recent one requiring O(Nϵ−2/3 + ϵ−8/3) que...
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The lack of affordable communication facilities to the shore remains a fundamental problem for fishermen engaged in deep-sea fishing. The Offshore Communication Network (OCN) is a wireless network of fishing vessels, ...
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