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An efficient facial emotion recognition using convolutional neural network with local sorting binary pattern and whale optimization algorithm
Facial emotion recognition is one of the fields of machine learning and pattern recognition. Facial expression recognition is used in a variety of...
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Exploration and Exploitation of Unlabeled Data for Open-Set Semi-supervised Learning
In this paper, we address a complex but practical scenario in semi-supervised learning (SSL) named open-set SSL, where unlabeled data contain both...
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DTS: dynamic training slimming with feature sparsity for efficient convolutional neural network
Deep convolutional neural networks have achieved remarkable progress on computer vision tasks over last years. In this paper, we proposed a dynamic...
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Omni-dimensional dynamic convolution feature coordinate attention network for pneumonia classification
Pneumonia is a serious disease that can be fatal, particularly among children and the elderly. The accuracy of pneumonia diagnosis can be improved by...
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Distributed source DOA estimation based on deep learning networks
With space electromagnetic environments becoming increasingly complex, the direction of arrival (DOA) estimation based on the point source model can...
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Infproto-Powered Adaptive Classifier and Agnostic Feature Learning for Single Domain Generalization in Medical Images
Designing a single domain generalization (DG) framework that generalizes from one source domain to arbitrary unseen domains is practical yet...
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Recent advances in 3D Gaussian splatting
The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel view synthesis. Unlike neural implicit representations like...
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Granular Syntax Processing with Multi-Task and Curriculum Learning
Syntactic processing techniques are the foundation of natural language processing (NLP), supporting many downstream NLP tasks. In this paper, we...
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IAFPN: interlayer enhancement and multilayer fusion network for object detection
Feature pyramid network (FPN) improves object detection performance by means of top-down multilevel feature fusion. However, the current FPN-based...
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CSSLnO: Cat Swarm Sea Lion Optimization-based deep learning for fake news detection from social media
Social media has effectively shortened the time for the distribution of information, which sometimes carry news when compared to traditional methods....
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Robust seamless GEO scanning control strategy for airborne electro-optical/infrared reconnaissance systems
Airborne electro-optical/infrared reconnaissance systems could scan a large area by using an array detector and stitching the image sequence to...
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GOA-net: generic occlusion aware networks for visual tracking
Occlusion is a frequent phenomenon that hinders the task of visual object tracking. Since occlusion can be from any object and in any shape, data...
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Truncated loss-based Res2Net for non-Gaussian noise removal
Many current image denoising works focus on Gaussian noise removal. However, in many real-life applications, the noise in an image can follow...
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A fast verifiable fully homomorphic encryption technique for secret computation on cloud data
In the domain of cloud computing, safeguarding the confidentiality and integrity of outsourced sensitive data during computational processes is of...
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Twin Bounded Support Vector Machine with Capped Pinball Loss
In order to obtain a more robust and sparse classifier, in this paper, we propose a novel classifier termed as twin bounded support vector machine...
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A FairMOT approach based on video recognition for real-time automatic incident detection on expressways
An accurate, fast and real-time expressway automatic incident detection (AID) algorithm can not only reduce the burden of expressway management...
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Robot remote control using virtual reality headset: studying sense of agency with subjective distance estimates
Mobile robots have many applications in the modern world. The autonomy of robots is increasing, but critical cases like search and rescue missions...
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AFS-BM: enhancing model performance through adaptive feature selection with binary masking
We study the problem of feature selection in general machine learning (ML) context, which is one of the most critical subjects in the field....
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Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks
This article examines the prescribed-time sampled-data control problem for multi-agent systems in signed networks. A time-varying high gain-based...
