Micro-expression recognition method based on progressive attention by ZHAN Ziwei, SUN Zhaocai, LI Xiang, WU Zhendong

“…First, the multi-scale convolutional module is used to learn fine-grained features from different receptive fields, extracting rich details. …”
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From Social to Academic: Associations and Predictions Between Different Types of Peer Relationships and Academic Performance Among College Students by Jiadong Tian, Jiali Lin, Dagang Li

“…This study aims to expose the correlation between different types of social behaviors and the academic performance of college students, and then to predict the academic performance of college students based on their social characteristics. …”
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Protective Effects of Withania Somnifera Against Cisplatin-Induced Acute Kidney Injury in Rats: A Histomorphometric Analysis by Aaqiba Rasheed, Nadia Younus, Nausheen Jamshed, Lubna Faisal, Naureen Waseem, Rana Muhammad Zeeshan, Omar Shamim

“…There was a decrease in the mean Proximal convoluted tubule count and Proximal convoluted tubule cell count of Cisplatin treated group.  …”
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Automated orofacial virtual patient creation using two cohorts of MSCT vs. CBCT scans by Thanatchaporn Jindanil, Oana-Elena Burlacu-Vatamanu, Benedetta Baldini, Joeri Meyns, Jeroen Meewis, Rocharles Cavalcante Fontenele, Maria Cadenas de Llano Perula, Reinhilde Jacobs

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DA-ResNeXt50 method for radio frequency fingerprint identification based on time-frequency and bispectral feature fusion by CHEN Mengdi, ZHANG Wei, SHEN Lei, LEI Fuqiang, ZHANG Jiafei

“…Borrowing from the idea of dense connection, each layer of the four-layer residual unit was directly connected to all previous layers, promoting feature reuse and transmission, which enabled it to better capture subtle differences between classes. Finally, the asymmetric convolution block (ACBlock) was used to replace the 3×3 convolution in the last residual unit of the model. …”
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Constructing an artificial intelligence-assisted system for the assessment of gastroesophageal valve function based on the hill classification (with video) by Jian Chen, Ganhong Wang, Kaijian Xia, Zhenni Wang, Luojie Liu, Xiaodan Xu

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Effective Algorithm for Biomedical Image Segmentation by Zhao Di, Tang Yi, A. B. Gourinovitch

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PermQRDroid: Android malware detection with novel attention layered mini-ResNet architecture over effective permission information image by Kazım Kılıç, İbrahim Alper Doğru, Sinan Toklu

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Working-memory load decoding model inspired by brain cognition based on cross-frequency coupling by Jing Zhang, Tingyi Tan, Yuhao Jiang, Congming Tan, Liangliang Hu, Daowen Xiong, Yikang Ding, Guowei Huang, Junjie Qin, Yin Tian

“…Drawing inspiration from the role of cross-frequency coupling in the hippocampal region, which plays a crucial role in advanced cognitive processes such as working memory, this study proposes a Multi-Band Multi-Scale Hybrid Sinc Convolutional Neural Network (MBSincNex). This model integrates multi-frequency and multi-scale Sinc convolution to facilitate time-frequency conversion and extract time-frequency information from multiple rhythms and regions of the EEG data with the aim of effectively model the cross-frequency coupling across different cognitive domains. …”
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Algorithm for pixel-level concrete pavement crack segmentation based on an improved U-Net model by Zixuan Zhang, Yike He, Di Hu, Qiang Jin, Manxu Zhou, Zongwei Liu, Hongli Chen, He Wang, Xinchen Xiang

“…Abstract Cracks that occur in concrete surfaces are numerous and diverse, and different cracks will affect road safety in different degrees. …”
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Exploring Generative Adversarial Network-Based Augmentation of Magnetic Resonance Brain Tumor Images by Mahnoor Mahnoor, Oona Rainio, Riku Klén

“…Background: A generative adversarial network (GAN) has gained popularity as a data augmentation technique in the medical field due to its efficiency in creating synthetic data for different machine learning models. In particular, the earlier literature suggests that the classification accuracy of a convolutional neural network (CNN) used for detecting brain tumors in magnetic resonance imaging (MRI) images increases when GAN-generated images are included in the training data together with the original images. …”
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Tunnel Crack Segmentation Algorithm Based on Feature Enhancement by Lihua Feng, Aijun Yao, An Huang

“…Lastly, the Adaptive Switchable Atrous Convolution (ASAC) module is introduced, combining the advantages of adaptive convolution and deformable convolution while incorporating Switchable Atrous Convolution (SAC) to enhance multi-scale feature capturing capabilities. …”
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Deep Learning Framework for Oil Shale Pyrolysis State Recognition Using Bionic Electronic Nose by Yuping Yuan, Xiaohui Weng, Yuheng Qiao, Xiaohu Shi, Zhiyong Chang

“…The proposed solution integrates Graph Convolutional Network (GCN) and Long Short-Term Memory (LSTM) to capture the spatial correlations among different sensors in the electronic nose and the temporal characteristics of the data, respectively. …”
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MoAGL-SA: a multi-omics adaptive integration method with graph learning and self attention for cancer subtype classification by Lei Cheng, Qian Huang, Zhengqun Zhu, Yanan Li, Shuguang Ge, Longzhen Zhang, Ping Gong

“…Next, three-layer graph convolutional networks are employed to extract omic-specific graph embeddings. …”
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Multi-Class Skin Cancer Classification Using a Hybrid Dynamic Salp Swarm Algorithm and Weighted Extreme Learning Machines with Transfer Learning by Ramya Panneerselvam, Sathiyabhama Balasubramaniam

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An air target intention data extension and recognition model based on deep learning by Bo Cao, Qinghua Xing, Longyue Li, Weijie Lin

“…Finally, the temporal block based on dilated causal convolution is built to solve the problem of temporal feature extraction. …”
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SparkNet–A Solar Panel Fault Detection Deep Learning Model by Rohith G, Dikshithula Sai Manish, Rahul Narasimhan A, Anurag Uttam Dhavale, Rohan Reji John

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Machine vision-based automatic fruit quality detection and grading by Amna, Muhammad Waqar AKRAM, Guiqiang LI, Muhammad Zuhaib AKRAM, Muhammad FAHEEM, Muhammad Mubashar OMAR, Muhammad Ghulman HASSAN

“…Image processing algorithms and deep learning frameworks were used for detection of defective fruit. Different image processing algorithms including pre-processing, thresholding, morphological and bitwise operations combined with a deep leaning algorithm, i.e., convolutional neural network (CNN), were applied to fruit images for the detection of defective fruit. …”
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An ensemble deep learning model for author identification through multiple features by Yuan Zhang

“…Our approach enhances generalization to a great extent by combining a wide range of writing styles representations such as statistical features, TF-IDF vectors, and Word2Vec embeddings. The different sets of features are fed through separate Convolutional Neural Networks (CNN) so that the specific stylistic features can be extracted. …”
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Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis by Wai Ying Kot, Sum Yin Au Yeung, Yin Yan Leung, Pui Hang Leung, Wei-fa Yang

“…Various deep learning algorithms were categorized according to the backbone network, encompassing single-stage convolutional models, convolutional models with U-Net architecture, Transformer models, convolutional models with attention mechanisms, and combinations of multiple models. …”
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