Development of a multi-level feature fusion model for basketball player trajectory tracking by Tao Wang

“…Then, a hybrid branch network was introduced to improve the residual network and a new athlete identity recognition model was proposed. …”
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Target Detection Algorithm Based on Global Feature Fusion in Parallel Dual Path Backbone by QIU Yunfei, XIN Hao

“…Then, the global scale information is gathered, which is integrated into different layers of features by using self-attention mechanism, and repeated many times to construct the neck network structure of global feature fusion, which effectively improves the ability of neck network to fuse global context information. …”
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Joint Sampling and Transmission Policies for Minimizing Cost Under Age of Information Constraints by Emmanouil Fountoulakis, Marian Codreanu, Anthony Ephremides, Nikolaos Pappas

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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…According to the relationship between the optimal value interval of the loss function and the training time, the optimal quantization series and the optimal bandwidth allocation strategy are obtained by solving the training time minimization problem. 2. For the user scheduling problem, the proposed user scheduling (TLM) scheme is compared with three other common scheduling schemes in the simulation, and the average precision is shown when the communication time is 6 000 s and 14 000 s, where the average Accuracy is obtained by measuring the IoU, the intersection of union, of the predicted value and the true value. …”
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An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion by Kavita Rawat, Trapti Sharma

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An Intelligent Weed Recognition Method Based on Optical Patrol Image by Guoliang YUE, Yanqiao LU, Hao CHANG, Cuiying SUN

“…Based on the feature of weeds in the optical images, and combined with the convolutional neural network method, the problem of weed recognition near the power equipment in optical patrol images is solved. …”
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Enhancing Multi-Label Chest X-Ray Classification Using an Improved Ranking Loss by Muhammad Shehzad Hanif, Muhammad Bilal, Abdullah H. Alsaggaf, Ubaid M. Al-Saggaf

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Categorical classification of skin cancer using a weighted ensemble of transfer learning with test time augmentation by Aliyu Tetengi Ibrahim, Mohammed Abdullahi, Armand Florentin Donfack Kana, Mohammed Tukur Mohammed, Ibrahim Hayatu Hassan

“…Due to the striking similarities between benign and malignant lesions, skin cancer detection remains a problem, even for expert dermatologists. Considering the inability of dermatologists to diagnose skin cancer accurately, a convolutional neural network (CNN) approach was used for skin cancer diagnosis. …”
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Social Interactions for Sustainable Food Choices: Meeting the Target for Meat Intake in the United Kingdom by Angela Fontan, Rosemary Green, Karl H Johansson, Patricia Eustachio Colombo

“…Methods: We considered the problem of influencing the opinions of a group of agents (representing the UK population) connected in a social network over a sequence of campaigns to achieve convergence to 2 different targets: achieving the UK Climate Change Committee’s goal of 35% and 50% average reduction in meat consumption by 2030 and 2050, respectively. …”
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Anti-Jamming RIS Communications Using DQN-Based Algorithm by Pham Duy Thanh, Hoang Thi Huong Giang, Ic-Pyo Hong

“…To this end, we formulate an anti-jamming communication optimization problem as a Markov decision process (MDP) framework and then design a deep Q network (DQN)-based algorithm to generate an optimal policy. …”
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Dual-Branch Deep Learning with Dynamic Stage Detection for CT Tube Life Prediction by Zhu Chen, Yuedan Liu, Zhibin Qin, Haojie Li, Siyuan Xie, Litian Fan, Qilin Liu, Jin Huang

“…To address these issues, this paper proposes an intelligent prediction architecture for CT tubes’ remaining useful life based on a dual-branch neural network. This architecture consists of two specialized branches: a residual self-attention BiLSTM (RSA-BiLSTM) and a multi-layer dilation temporal convolutional network (D-TCN). …”
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Research on Multi-Scale Point Cloud Completion Method Based on Local Neighborhood Dynamic Fusion by Yalun Liu, Jiantao Sun, Ling Zhao

“…Finally, when designing the decoder, inspired by the concept of generative adversarial networks (GANs), an attention discriminator designed in series with a feature extraction layer and an attention layer is added to further optimize the completion performance of the network. …”
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Fault diagnosis of ZDJ7 railway point machine based on improved DCNN and SVDD classification by Zengshu Shi, Yiman Du, Xinwen Yao

“…Abstract Problems such as poor noise immunity and overfitting are prone to occur when convolutional neural network (CNN) is exploited in the fault diagnosis of ZDJ7 railway point machine. …”
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A green hydrogen production model from solar powered water electrolyze based on deep chaotic Lévy gazelle optimization by Heba Askr, Mahmoud Abdel-Salam, Václav Snášel, Aboul Ella Hassanien

“…DeepGaz combines a new Chaotic-Lévy variant of the gazelle optimization algorithm (CGOA) with a recurrent neural network (RNN/LSTM) for hyperparameter optimization. …”
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Modeling and Predicting Time Series with Non-stationarity and Volatility by FENG Qiang, ZHAO Jianguang, YANG Rong, NIU Baoning

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Solar PV’s Micro Crack and Hotspots Detection Technique Using NN and SVM by David Prince Winston, Madhu Shobini Murugan, Rajvikram Madurai Elavarasan, Rishi Pugazhendhi, O. Jeba Singh, Pravin Murugesan, M. Gurudhachanamoorthy, Eklas Hossain

“…Both methods exhibited a promising result with an average accuracy of 87% for feed-forward back propagation neural network and 99% SVM technique which exposes the potential of this proposed technique.…”
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HP-ECD: Heuristic Prophet protocol based on energy balance,cache optimization, and asynchronous dormancy by Jingjian Chen, Pengfei Bie, Jie Nie, Zhiqiang Wei

“…In opportunistic networks, opportunistic routing protocols are used for nodes to forward messages, which are the core technology to realize various opportunistic network applications. …”
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Anomaly Detection Over Multi-Relational Graphs Using Graph Structure Learning and Multi-Scale Meta-Path Graph Aggregation by Chi Zhang, Junho Jeong, Jin-Woo Jung

“…Graph Neural Networks (GNNs) have recently achieved remarkable success in various learning tasks involving graph-structured data. …”
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A deep learning-based data augmentation method for marine mammal call signals by Jiaming Jiang, Jiaming Jiang, Wanlu Cheng, Wanlu Cheng, Shengwen Gong, Shengwen Gong, Jingjing Wang, Jingjing Wang

“…This method processed the call data into Mel spectrograms, then designed a self-attention conditional generative adversarial network to generate new samples of Mel spectrograms that were highly similar to the real data, and finally reconstructed them into call signals using WaveGlow. …”
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G2Grad-CAMRL: An Object Detection and Interpretation Model Based on Gradient-Weighted Class Activation Mapping and Reinforcement Learning in Remote Sensing Images by Shoulin Yin, Liguo Wang, Muhammad Shafiq, Lin Teng, Asif Ali Laghari, Muhammad Faizan Khan

“…Aiming at the complex background of RSIs and the lack of interpretability of existing target detection models, and the problems in feature extraction between different network structures, different layers, and the accuracy of target classification, we propose an object detection and interpretation model based on gradient-weighted class activation mapping and reinforcement learning. …”
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