Multi-featured spatial-temporal and dynamic multi-graph convolutional network for metro passenger flow prediction by Chuan Zhao, Xin Li, Zezhi Shao, HongJi Yang, Fei Wang

“…To address these challenges, we developed a novel model called the multi-featured spatial-temporal (MFST) and dynamic multi-graph convolutional network (DMGCN) model. …”
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RecNet: Reinforcement Common Feature Mapping Network for Fast Template Matching in Visible-LWIR Images by Donyung Kim, Seungeon Lee, Inho Park, Geonjong Kim, Sungho Kim

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Sparse convolutional neural network acceleration with lossless input feature map compression for resource‐constrained systems by Jisu Kwon, Joonho Kong, Arslan Munir

“…Abstract Many recent research efforts have exploited data sparsity for the acceleration of convolutional neural network (CNN) inferences. However, the effects of data transfer between main memory and the CNN accelerator have been largely overlooked. …”
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DEFIF-Net: A lightweight dual-encoding feature interaction fusion network for medical image segmentation. by Zhanlin Ji, Shengnan Hao, Quanming Zhao, Zidong Yu, Hongjiu Liu, Lei Li, Ivan Ganchev

“…Lastly, a novel residual feature enhancement (RFE) decoder is utilized to emphasize boundary features, thereby increasing the network's sensitivity to lesion boundaries. …”
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PhishingGNN: Phishing Email Detection Using Graph Attention Networks and Transformer-Based Feature Extraction by Mejdl Safran, Abdulbaset Musleh

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IMpc-PyrYOLO: Hybrid YOLO Based Feature Pyramidal Network for Pest Detection in Rice Leaves by Ramesh Shunmugam, Sumendra Yogarayan, Siti Fatimah Abdul Razak, Md. Shohel Sayeed

“…The model integrates an efficient channel attention (ECA) mechanism with the feature pyramidal network (FPN) in the YOLO network to improve multi-scale feature extraction and pest classification accuracy. …”
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Attention-Guided Sample-Based Feature Enhancement Network for Crowded Pedestrian Detection Using Vision Sensors by Shuyuan Tang, Yiqing Zhou, Jintao Li, Chang Liu, Jinglin Shi

“…To address this, we introduce a novel architecture termed the Attention-Guided Feature Enhancement Network (AGFEN), designed within the deep convolutional neural network framework. …”
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Melanoma Skin Cancer Recognition with a Convolutional Neural Network and Feature Dimensions Reduction with Aquila Optimizer by Jalaleddin Mohamed, Necmi Serkan Tezel, Javad Rahebi, Raheleh Ghadami

“…This study aims to develop a novel classification system for melanoma detection that integrates Convolutional Neural Networks (CNNs) for feature extraction and the Aquila Optimizer (AO) for feature dimension reduction, improving both computational efficiency and classification accuracy. …”
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Toward Efficient UAV-Based Small Object Detection: A Lightweight Network with Enhanced Feature Fusion by Xingyu Di, Kangning Cui, Rui-Feng Wang

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Early breast cancer detection in CT scans using convolutional neural bidirectional feature pyramid network by Tahani Jaser Alahmadi, Adeel Ahmed, Amjad Rehman, Abeer Rashad Mirdad, Bayan Al Ghofaily, Shehryar Ali

“…In this article, we proposed a framework called convolutional neural bidirectional feature pyramid network, which integrates multi-scale feature extraction and bidirectional feature fusion for breast cancer detection in CT scans. …”
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Transformer-Based Dual-Branch Spatial–Temporal–Spectral Feature Fusion Network for Paddy Rice Mapping by Xinxin Zhang, Hongwei Wei, Yuzhou Shao, Haijun Luan, Da-Han Wang

“…Deep neural network fusion approaches utilizing multimodal remote sensing are essential for crop mapping. …”
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Topic adversarial neural network for cross-topic cyberbullying detection by Shufeng Xiong, Wenzhuo Liu, Bingkun Wang, Yinchao Che, Lei Shi

“…Most existing methods struggle to generalize across diverse online contexts due to their reliance on topic-specific features. To address this issue, we propose the Topic Adversarial Neural Network (TANN), a novel end-to-end framework for topic-invariant cyberbullying detection. …”
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Evaluating Security Anomalies by Classifying Traffic Using a Multi-Layered Model by Mohammadreza Samadzadeh, Najmeh Farajipour Ghohroud

“…In the second step, the proposed method uses the features extracted by the autoencoder from a hybrid deep-learning model based on the CNN and LSTM algorithms to classify network traffic. …”
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Tunnel Crack Segmentation Algorithm Based on Feature Enhancement by Lihua Feng, Aijun Yao, An Huang

“…Firstly, a novel Dynamic Feature Enhancement Network (DFEN) module is designed to extract preliminary features using a feature extractor and selectively enhance feature representations through a gating mechanism. …”
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Anomaly Detection Approach Based on Deep Neural Network and Dropout by Zaid Hussien et al.

“…They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. …”
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Implementation and Evaluation of WLAN 802.11ac for Residential Networks in NS-3 by Andy Bubune Amewuda, Ferdinand Apietu Katsriku, Jamal-Deen Abdulai

“…We also evaluate the average throughput, delay, jitter, optimum range for goodput, and effect of station (STA) density per access point (AP) in a network. ns-3, an open source network simulator with features supporting 802.11ac, was used to perform the simulation. …”
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Longitudinal evaluation of common and unique brain-networks in variants of primary progressive aphasia by Rajan Kashyap, Rose Dawn Bharath, Changsong Zhou, Kyrana Tsapkini, John E. Desmond, SH Annabel Chen, Kaviraja Udupa, PT Sivakumar, Sagarika Bhattacharjee

“…Since the subset of these subjects was scanned at the 6th and 12th months, the longitudinal changes in the rsfMRI networks were evaluated at each interval. Network features were correlated with clinical behaviours, and the longitudinal impact of the changes in these networks on behaviours was evaluated over the 12-month period. …”
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The node importance evaluation method based on graph convolution in multilayer heterogeneous networks by Zhixing Chen, Jian Shu, Linlan Liu

“…Node importance evaluation is a hot issue in complex network analysis. …”
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Integration of MRMR algorithm with advanced neural networks for modeling long-term crop water demand in agricultural basins by Ahmed Elbeltagi, Abdullah A. Alsumaiei, Ali Raza, Mustafa Al-Mukhtar, Salim Heddam

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Research on Objective Evaluation of Recording Audio Restoration Based on Deep Learning Network by Cong Jin, Wei Zhao, Hongliang Wang

“…Based on the deep learning network, this paper designs an objective quality evaluation system for historical audio and video data and evaluates the performance of the system and the audio signal quality from the perspective of feature extraction and network parameter selection. …”
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