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Efficient Visual Metaphor Image Generation Based on Metaphor Understanding Neural Process Lett. (IF 3.1) Pub Date : 2024-04-16 Chang Su, Xingyue Wang, Shupin Liu, Yijiang Chen
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SSGAN: A Semantic Similarity-Based GAN for Small-Sample Image Augmentation Neural Process Lett. (IF 3.1) Pub Date : 2024-04-16 Congcong Ma, Jiaqi Mi, Wanlin Gao, Sha Tao
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Learning Reliable Dense Pseudo-Labels for Point-Level Weakly-Supervised Action Localization Neural Process Lett. (IF 3.1) Pub Date : 2024-04-10 Yuanjie Dang, Guozhu Zheng, Peng Chen, Nan Gao, Ruohong Huan, Dongdong Zhao, Ronghua Liang
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Novel GCN Model Using Dense Connection and Attention Mechanism for Text Classification Neural Process Lett. (IF 3.1) Pub Date : 2024-04-09 Yinbin Peng, Wei Wu, Jiansi Ren, Xiang Yu
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DialGNN: Heterogeneous Graph Neural Networks for Dialogue Classification Neural Process Lett. (IF 3.1) Pub Date : 2024-04-08 Yan Yan, Bo-Wen Zhang, Peng-hao Min, Guan-wen Ding, Jun-yuan Liu
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Consensus Affinity Graph Learning via Structure Graph Fusion and Block Diagonal Representation for Multiview Clustering Neural Process Lett. (IF 3.1) Pub Date : 2024-04-08 Zhongyan Gui, Jing Yang, Zhiqiang Xie, Cuicui Ye
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Semantic Spectral Clustering with Contrastive Learning and Neighbor Mining Neural Process Lett. (IF 3.1) Pub Date : 2024-04-07 Nongxiao Wang, Xulun Ye, Jieyu Zhao, Qing Wang
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SGNNRec: A Scalable Double-Layer Attention-Based Graph Neural Network Recommendation Model Neural Process Lett. (IF 3.1) Pub Date : 2024-04-04 Jing He, Le Tang, Dan Tang, Ping Wang, Li Cai
Due to the information from the multi-relationship graphs is difficult to aggregate, the graph neural network recommendation model focuses on single-relational graphs (e.g., the user-item rating bipartite graph and user-user social relationship graphs). However, existing graph neural network recommendation models have insufficient flexibility. The recommendation accuracy instead decreases when low-quality
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Efficient Bayesian CNN Model Compression using Bayes by Backprop and L1-Norm Regularization Neural Process Lett. (IF 3.1) Pub Date : 2024-04-04 Ali Muhammad Shaikh, Yun-bo Zhao, Aakash Kumar, Munawar Ali, Yu Kang
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Hierarchical Patch Aggregation Transformer for Motion Deblurring Neural Process Lett. (IF 3.1) Pub Date : 2024-04-04 Yujie Wu, Lei Liang, Siyao Ling, Zhisheng Gao
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Detection and Classification of Brain Tumor Using Convolution Extreme Gradient Boosting Model and an Enhanced Salp Swarm Optimization Neural Process Lett. (IF 3.1) Pub Date : 2024-04-02 J. Jebastine
Some types of tumors in people with brain cancer grow so rapidly that their average size doubles in twenty-five days. Precisely determining the type of tumor enables physicians to conduct clinical planning and estimate dosage. However, accurate classification remains a challenging task due to the variable shape, size, and location of the tumors.The major objective of this paper is to detect and classify
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A New Adaptive Robust Modularized Semi-Supervised Community Detection Method Based on Non-negative Matrix Factorization Neural Process Lett. (IF 3.1) Pub Date : 2024-04-02
Abstract The most extensively used tools for categorizing complicated networks are community detection methods. One of the most common methods for unsupervised and semi-supervised clustering is community detection based on Non-negative Matrix Factorization (NMF). Nonetheless, this approach encounters multiple challenges, including the lack of specificity for the data type and the decreased efficiency
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Human Gait Recognition Based on Frontal-View Walking Sequences Using Multi-modal Feature Representations and Learning Neural Process Lett. (IF 3.1) Pub Date : 2024-04-02
Abstract Despite that much progress has been reported in gait recognition, most of these existing works adopt lateral-view parameters as gait features, which requires large area of data collection environment and limits the applications of gait recognition in real-world practice. In this paper, we adopt frontal-view walking sequences rather than lateral-view sequences and propose a new gait recognition
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Multi-Model UNet: An Adversarial Defense Mechanism for Robust Visual Tracking Neural Process Lett. (IF 3.1) Pub Date : 2024-04-01 Wattanapong Suttapak, Jianfu Zhang, Haohuo Zhao, Liqing Zhang
Currently, state-of-the-art object-tracking algorithms are facing a severe threat from adversarial attacks, which can significantly undermine their performance. In this research, we introduce MUNet, a novel defensive model designed for visual tracking. This model is capable of generating defensive images that can effectively counter attacks while maintaining a low computational overhead. To achieve
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Self-Enhanced Attention for Image Captioning Neural Process Lett. (IF 3.1) Pub Date : 2024-04-01
Abstract Image captioning, which involves automatically generating textual descriptions based on the content of images, has garnered increasing attention from researchers. Recently, Transformers have emerged as the preferred choice for the language model in image captioning models. Transformers leverage self-attention mechanisms to address gradient accumulation issues and eliminate the risk of gradient
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Deep Self-Supervised Attributed Graph Clustering for Social Network Analysis Neural Process Lett. (IF 3.1) Pub Date : 2024-04-01 Hu Lu, Haotian Hong, Xia Geng
Deep graph clustering is an unsupervised learning task that divides nodes in a graph into disjoint regions with the help of graph auto-encoders. Currently, such methods have several problems, as follows. (1) The deep graph clustering method does not effectively utilize the generated pseudo-labels, resulting in sub-optimal model training results. (2) Each cluster has a different confidence level, which
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Global Asymptotic Stability of Anti-Periodic Solutions of Time-Delayed Fractional Bam Neural Networks Neural Process Lett. (IF 3.1) Pub Date : 2024-03-30 Münevver Tuz
In this study, bidirectional fractional-order BAM neural networks with time-varying delays are examined. Time delay is an important phenomenon in the implementation of a signal or effect passing through neural network. Signal transmission in neural networks can generally be described as an anti-periodic process. Our aim is to show global asymptotic stability and the uniqueness of the equilibrium point
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Deep Embedding Clustering Based on Residual Autoencoder Neural Process Lett. (IF 3.1) Pub Date : 2024-03-30
Abstract Clustering algorithm is one of the most widely used and influential analysis techniques. With the advent of deep learning, deep embedding clustering algorithms have rapidly evolved and yield promising results. Much of the success of these algorithms depends on the potential expression captured by the autoencoder network. Therefore, the quality of the potential expression directly determines
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Central Attention with Multi-Graphs for Image Annotation Neural Process Lett. (IF 3.1) Pub Date : 2024-03-30 Baodi Liu, Yan Liu, Qianqian Shao, Weifeng Liu
In recent decades, the development of multimedia and computer vision has sparked significant interest among researchers in the field of automatic image annotation. However, much of the research has primarily focused on using a single graph for annotating images in semi-supervised learning. Conversely, numerous approaches have explored the integration of multi-view or image segmentation techniques to
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Improved Lightweight Head Detection Based on GhostNet-SSD Neural Process Lett. (IF 3.1) Pub Date : 2024-03-29
Abstract This abstract proposes an algorithm for human head detection in elevator cabins that addresses the challenges of improving detection accuracy, reducing detection speed, and decreasing the number of parameters. The algorithm is based on GhostNet-SSD and includes several improvements, such as an efficient coordinate attention mechanism to replace the Squeeze-and-Excitation attention mechanism
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Power Optimization in Wireless Sensor Network Using VLSI Technique on FPGA Platform Neural Process Lett. (IF 3.1) Pub Date : 2024-03-28 Saranya Leelakrishnan, Arvind Chakrapani
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Multipath Attention and Adaptive Gating Network for Video Action Recognition Neural Process Lett. (IF 3.1) Pub Date : 2024-03-27 Haiping Zhang, Zepeng Hu, Dongjin Yu, Liming Guan, Xu Liu, Conghao Ma
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Reconstruction-Aware Kernelized Fuzzy Clustering Framework Incorporating Local Information for Image Segmentation Neural Process Lett. (IF 3.1) Pub Date : 2024-03-27 Chengmao Wu, Xiao Qi
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Extended dissipative criteria for delayed semi-discretized competitive neural networks Neural Process Lett. (IF 3.1) Pub Date : 2024-03-25 B. Adhira, G. Nagamani
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Neural Data Augmentation for Legal Overruling Task: Small Deep Learning Models vs. Large Language Models Neural Process Lett. (IF 3.1) Pub Date : 2024-03-23
Abstract Deep learning models produce impressive results in any natural language processing applications when given a better learning strategy and trained with large labeled datasets. However, the annotation of massive training data is far too expensive, especially in the legal domain, due to the need for trained legal professionals. Data augmentation solves the problem of learning without labeled
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Causality-Driven Intra-class Non-equilibrium Label-Specific Features Learning Neural Process Lett. (IF 3.1) Pub Date : 2024-03-21 Wenxin Ge, Yibin Wang, Yuting Xu, Yusheng Cheng
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A Novel Distributed Process Monitoring Framework of VAE-Enhanced with Deep Neural Network Neural Process Lett. (IF 3.1) Pub Date : 2024-03-20 Ming Yin, Jiayi Tian, Yibo Wang, Jijiao Jiang
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Robustness analysis of exponential stability of fuzzy inertial neural networks through the estimation of upper limits of perturbations Neural Process Lett. (IF 3.1) Pub Date : 2024-03-20 Wenxiang Fang, Tao Xie
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Hyperspectral Image Classification Based on 3D–2D Hybrid Convolution and Graph Attention Mechanism Neural Process Lett. (IF 3.1) Pub Date : 2024-03-20 Hui Zhang, Kaiping Tu, Huanhuan Lv, Ruiqin Wang
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Intuitionistic Fuzzy Extreme Learning Machine with the Truncated Pinball Loss Neural Process Lett. (IF 3.1) Pub Date : 2024-03-20 Qingyun Gao, Qing Ai, Wenhui Wang
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Boundedness and Convergence of Mini-batch Gradient Method with Cyclic Dropconnect and Penalty Neural Process Lett. (IF 3.1) Pub Date : 2024-03-19 Junling Jing, Cai Jinhang, Huisheng Zhang, Wenxia Zhang
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CNN-based Methods for Offline Arabic Handwriting Recognition: A Review Neural Process Lett. (IF 3.1) Pub Date : 2024-03-19 Mohsine El Khayati, Ismail Kich, Youssef Taouil
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Enhanced Coalescence Backdoor Attack Against DNN Based on Pixel Gradient Neural Process Lett. (IF 3.1) Pub Date : 2024-03-19 Jianyao Yin, Honglong Chen, Junjian Li, Yudong Gao
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Detection of Image Tampering Using Deep Learning, Error Levels and Noise Residuals Neural Process Lett. (IF 3.1) Pub Date : 2024-03-19 Sunen Chakraborty, Kingshuk Chatterjee, Paramita Dey
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Stabilization of Semi-Markovian Jumping Uncertain Complex-Valued Networks with Time-Varying Delay: A Sliding-Mode Control Approach Neural Process Lett. (IF 3.1) Pub Date : 2024-03-18 Qiang Li, Hanqing Wei, Dingli Hua, Jinling Wang, Junxian Yang
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CLSTM-SNP: Convolutional Neural Network to Enhance Spiking Neural P Systems for Named Entity Recognition Based on Long Short-Term Memory Network Neural Process Lett. (IF 3.1) Pub Date : 2024-03-18 Qin Deng, Xiaoliang Chen, Zaiyan Yang, Xianyong Li, Yajun Du
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A Feature Selection Method Based on Feature-Label Correlation Information and Self-Adaptive MOPSO Neural Process Lett. (IF 3.1) Pub Date : 2024-03-18 Fei Han, Fanyu Li, Qinghua Ling, Henry Han, Tianyi Lu, Zijian Jiao, Haonan Zhang
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Deep Reinforcement Learning Model for Stock Portfolio Management Based on Data Fusion Neural Process Lett. (IF 3.1) Pub Date : 2024-03-17 Haifeng Li, Mo Hai
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An Adaptive Learning Rate Deep Learning Optimizer Using Long and Short-Term Gradients Based on G–L Fractional-Order Derivative Neural Process Lett. (IF 3.1) Pub Date : 2024-03-15 Shuang Chen, Changlun Zhang, Haibing Mu
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Multi-modal Domain Adaptation Method Based on Parameter Fusion and Two-Step Alignment Neural Process Lett. (IF 3.1) Pub Date : 2024-03-15 Lan Wu, Han Wang, Lishuang Gong, Yuan Yao, Xin Guo, Binquan Li
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A New Optimization Model for MLP Hyperparameter Tuning: Modeling and Resolution by Real-Coded Genetic Algorithm Neural Process Lett. (IF 3.1) Pub Date : 2024-03-14 Fatima Zahrae El-Hassani, Meryem Amri, Nour-Eddine Joudar, Khalid Haddouch
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Dissipativity of Stochastic Competitive Neural Networks with Multiple Time Delays Neural Process Lett. (IF 3.1) Pub Date : 2024-03-14 Dandan Tang, Baoxian Wang, Caiqing Hao
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Deep Convolutional Neural Network Compression Method: Tensor Ring Decomposition with Variational Bayesian Approach Neural Process Lett. (IF 3.1) Pub Date : 2024-03-13
Abstract Due to deep neural networks (DNNs) a large number of parameters, DNNs increase the demand for computing and storage during training, reasoning and deployment, especially when DNNs stack deeper and wider. Tensor decomposition can not only compress DNN models but also reduce parameters and storage requirements while maintaining high accuracy and performance. About tensor ring (TR) decomposition
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Co-GZSL: Feature Contrastive Optimization for Generalized Zero-Shot Learning Neural Process Lett. (IF 3.1) Pub Date : 2024-03-12 Qun Li, Zhuxi Zhan, Yaying Shen, Bir Bhanu
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Multi-back-propagation Algorithm for Signal Neural Network Decomposition Neural Process Lett. (IF 3.1) Pub Date : 2024-03-12 Paulo Salgado, T.-P. Azevedo Perdicoúlis
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PEB-TAXO: Projecting Entities as Boxes for Taxonomy Expansion Neural Process Lett. (IF 3.1) Pub Date : 2024-03-12 Yuhang Zhang, Jiwei Qin, Chongren Feng
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Non-separation Method-Based Global Stability Criteria for Takagi–Sugeno Fuzzy Quaternion-Valued BAM Delayed Neural Networks Using Quaternion-valued Auxiliary Function-Based Integral Inequality Neural Process Lett. (IF 3.1) Pub Date : 2024-03-12 Sriraman Ramalingam, Oh-Min Kwon
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SiamRAAN: Siamese Residual Attentional Aggregation Network for Visual Object Tracking Neural Process Lett. (IF 3.1) Pub Date : 2024-03-11 Zhiyi Xin, Junyang Yu, Xin He, Yalin Song, Han Li
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CFGPFSR: A Generative Method Combining Facial and GAN Priors for Face Super-Resolution Neural Process Lett. (IF 3.1) Pub Date : 2024-03-09 Jinbo Liu, Zhonghua Liu, Weihua Ou, Kaibing Zhang, Yong Liu
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New Insights on Bidirectional Associative Memory Neural Networks with Leakage Delay Components and Time-Varying Delays Using Sampled-Data Control Neural Process Lett. (IF 3.1) Pub Date : 2024-03-07
Abstract The sampling data control of bidirectional associative memory (BAM) neural network with leakage delay is considered in this article. The BAM model is viewed as a mixed delay that combines a distributed delay, a discrete delay that varies over time, and a delay in the leaking period. The sampling system is then converted to a continuous time-delay system using an input delay method. In order
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Rethinking Zero-DCE for Low-Light Image Enhancement Neural Process Lett. (IF 3.1) Pub Date : 2024-03-07 Aizhong Mi, Wenhui Luo, Yingxu Qiao, Zhanqiang Huo
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Harmonious Mutual Learning for Facial Emotion Recognition Neural Process Lett. (IF 3.1) Pub Date : 2024-03-07
Abstract Facial emotion recognition in the wild is an important task in computer vision, but it still remains challenging since the influence of backgrounds, occlusions and illumination variations in facial images, as well as the ambiguity of expressions. This paper proposes a harmonious mutual learning framework for emotion recognition, mainly through utilizing attention mechanisms and probability
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Density-Based Discriminative Nonnegative Representation Model for Imbalanced Classification Neural Process Lett. (IF 3.1) Pub Date : 2024-03-07 Yanting Li, Shuai Wang, Junwei Jin, Hongwei Tao, Jiaofen Nan, Huaiguang Wu, C. L. Philip Chen
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CEEMDAN-Based Hybrid Machine Learning Models for Time Series Forecasting Using MARS Algorithm and PSO-Optimization Neural Process Lett. (IF 3.1) Pub Date : 2024-03-06 Sandip Garai, Ranjit Kumar Paul, Md Yeasin, A. K. Paul
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A Novel Boundary-Guided Global Feature Fusion Module for Instance Segmentation Neural Process Lett. (IF 3.1) Pub Date : 2024-03-06 Linchun Gao, Shoujun Wang, Songgui Chen
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HF-YOLO: Advanced Pedestrian Detection Model with Feature Fusion and Imbalance Resolution Neural Process Lett. (IF 3.1) Pub Date : 2024-03-06 Lihu Pan, Jianzhong Diao, Zhengkui Wang, Shouxin Peng, Cunhui Zhao
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A Correlation-Redundancy Guided Evolutionary Algorithm and Its Application to High-Dimensional Feature Selection in Classification Neural Process Lett. (IF 3.1) Pub Date : 2024-03-06 Xiang Sun, Shunsheng Guo, Shiqiao Liu, Jun Guo, Baigang Du
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DE3TC: Detecting Events with Effective Event Type Information and Context Neural Process Lett. (IF 3.1) Pub Date : 2024-03-06
Abstract Event Detection (ED) is a crucial information extraction task that aims to identify the event triggers and classify them into predefined event types. However, most existing methods did not perform well when processing events with implicit triggers. And most methods considered ED as a sentence-level task, lacking effective context for event semantics. Moreover, how to maintain good performance
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FEASE: Feature Selection and Enhancement Networks for Action Recognition Neural Process Lett. (IF 3.1) Pub Date : 2024-03-06 Lu Zhou, Yuanyao Lu, Haiyang Jiang
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Image Deblurring Using Feedback Mechanism and Dual Gated Attention Network Neural Process Lett. (IF 3.1) Pub Date : 2024-03-06 Jian Chen, Shilin Ye, Zhuwu Jiang, Zhenghan Fang