Triple-Stream Deep Feature Selection with Metaheuristic Optimization and Machine Learning for Multi-Stage Hypertensive Retinopathy Diagnosis by Süleyman Burçin Şüyun, Mustafa Yurdakul, Şakir Taşdemir, Serkan Biliş

“…In the first stage, 14 well-known Convolutional Neural Network (CNN) models were evaluated, and the top three models were identified. …”
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Multi-task meta-attention network for traditional Chinese medicine diagnostic recommendation by YingShuai Wang, YanLi Wan, HongPu Hu, HongPu Hu

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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…MobileNet, VGG16, NasNetMobile, DenseNet201, InceptionV3, and Xception were experimented with in the feature extraction and performance evaluation process. …”
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Evaluation of the Aspects of Digital Interventions That Successfully Support Weight Loss: Systematic Review With Component Network Meta-Analysis by Michael Nunns, Samantha Febrey, Rebecca Abbott, Jill Buckland, Rebecca Whear, Liz Shaw, Alison Bethel, Kate Boddy, Jo Thompson Coon, G.J. Melendez-Torres

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Speech emotion recognition with light weight deep neural ensemble model using hand crafted features by Jaher Hassan Chowdhury, Sheela Ramanna, Ketan Kotecha

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Ghost-Attention-YOLOv8: Enhancing Rice Leaf Disease Detection with Lightweight Feature Extraction and Advanced Attention Mechanisms by Thanh Dang Bui, Tra My Do Le

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Graph convolutional network model with a feature compensation module and dual-channel second-order pooling module for multimodal emotion recognition in conversation by Xiaocong Tan, Zhengze Gong, Mengkun Gan, Weijie Xie, Wenhui Wang

“…Consequently, this study developed a graph convolutional network (GCN) model with a feature compensation module and dual-channel second-order pooling module for MERC. …”
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LSKAFF-YOLO: Large Separable Kernel Attentional Feature Fusion Network for Transmission Tower Detection in High-Resolution Satellite Remote Sensing Images by Xiaojin Yan, Zhixuan Li, Yongjie Zhai, Ke Liu, Ke Zhang, Zhenbing Zhao

“…Moreover, a progressive path aggregation network replaces the original neck network, mitigating information loss or degradation during feature transfer and interaction, thereby realizing multiscale feature fusion of transmission towers. …”
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Risk assessment of thyroid nodules with a multi-instance convolutional neural network by Da Yu, Tingting Song, Yancheng Yu, Hebin Zhang, Feng Gao, Zirong Wang, Jiacheng Wang

“…This enables effective feature extraction and localization of key instance features, facilitating risk assessment of thyroid nodules. …”
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Multi-Head Attention-Based Framework with Residual Network for Human Action Recognition by Basheer Al-Tawil, Magnus Jung, Thorsten Hempel, Ayoub Al-Hamadi

“…It integrates residual networks (ResNet-18) for spatial feature extraction and Bi-LSTM for temporal feature extraction. …”
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Novel Approach in Vegetation Detection Using Multi-Scale Convolutional Neural Network by Fatema A. Albalooshi

“…This study explores the potential of a multi-scale convolutional neural network (MSCNN) design for object classification, specifically focusing on vegetation detection. …”
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Development of a Sound Quality Evaluation Model Based on an Optimal Analytic Wavelet Transform and an Artificial Neural Network by Mehdi POURSEIEDREZAEI, Ali LOGHMANI, Mehdi KESHMIRI

“…The feature matrix is fed into the neural network input to determine the psychoacoustic parameters used for sound quality evaluation. …”
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Characteristics Analysis of Mental Health Data of College Students Based on Convolutional Neural Network and TOPSIS Evaluation Model by Lanfeng Zhou

“…This paper develops a feature analysis method of the mental health data of students in different colleges and regions and of different ages based on a convolutional neural network and TOPSIS evaluation model and studies the college students’ mental health analysis model based on convolutional neural network. …”
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Comparative Evaluation of Feed-Forward Neural Networks for Predicting Uniaxial Compressive Strength of Seybaplaya Carbonate Rock Cores by Jose W. Naal-Pech, Leonardo Palemón-Arcos, Youness El Hamzaoui

“…This work presents a comprehensive evaluation of four feed-forward artificial neural network (ANN) architectures—radial basis function (RBF), Bayesian regularized (BR), scaled conjugate gradient (SCG), and Levenberg–Marquardt (LM)—to predict UCS from three readily measured variables: water content, interconnected porosity, and real density. …”
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CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China by Tongtong Shi, Ping Wang, Xudong Qi, Jiacheng Yang, Rui He, Jingwen Yang, Yu Han

“…The congestion prediction method is designed including two modules: a deep learning (DL) prediction and a fuzzy evaluation. We propose a modified deep learning method based on graph convolutional network (GCN) structure in the fusion of dilated causal mechanism and optimize the method for spatial feature extraction by constructing a new adjacency matrix. …”
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An improved lightweight tongue segmentation model with self-attention parallel network and progressive upsampling by Xuan Wang, Yifang Cao, Yijia Chen, Huixia Li, Aiqing Han, Yan Tang

“…The model incorporates three key enhancements: (1) the adoption of a Self-Attention Parallel Network that integrates the self-attention mechanism and residual modules to achieve simultaneous extraction of local and global features; (2) the integration of the Efficient Channel Attention(ECA) mechanism into the Mix-FFN component to enhance feature extraction efficiency; and (3) the utilization of Multi-dimensional Feature Progressive Upsampling to mitigate precision loss during the upsampling process. …”
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A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification by Neha Sharma, Manoj Sharma, Amit Singhal, Nuzhat Fatema, Vinay Kumar Jadoun, Hasmat Malik, Asyraf Afthanorhan

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Multimodal Fall Detection Using Spatial–Temporal Attention and Bi-LSTM-Based Feature Fusion by Jungpil Shin, Abu Saleh Musa Miah, Rei Egawa, Najmul Hassan, Koki Hirooka, Yoichi Tomioka

“…The GSTCAN model uses AlphaPose for skeleton extraction, calculates motion between consecutive frames, and applies a graph convolutional network (GCN) with a CA mechanism to focus on relevant features while suppressing noise. …”
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A Transformer-Based Multiscale Difference Enhancement Network for Change Detection by Mengyang Pan, Hang Yang, Chengkang Yu, Mingqing Li, Anping Deng

“…Despite the progress made by convolutional neural networks and Transformer architectures in visual analysis, challenges remain in achieving robust feature representation and global contextual understanding. …”
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Evaluation of machine learning algorithm capability for Bosten Lake Wetland classification based on multi-temporal Sentinel-2 data by Feiying Xia, Guanghui Lv

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