Research on the Application of Deep Learning Methods in the Field of Image Classification by Peng Yuhui

“…The application of deep learning methods such as Convolutional Neural Network, Recurrent Neural Networks and Long Short-Term Memory in image classification is also discussed. …”
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Time-Series Forecasting Method Based on Hierarchical Spatio-Temporal Attention Mechanism by Zhiguo Xiao, Junli Liu, Xinyao Cao, Ke Wang, Dongni Li, Qian Liu

“…This study innovatively proposes a Spatio-Temporal Attention-Enhanced Network (TSEBG). Breaking through traditional structural designs, the model employs a Squeeze-and-Excitation Network (SENet) to reconstruct the convolutional layers of the Temporal Convolutional Network (TCN), strengthening the feature expression of key time steps through dynamic channel weight allocation to address the redundancy issue of traditional causal convolutions in local pattern capture. …”
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Deep CNN and Deep GAN in Computational Visual Perception-Driven Image Analysis by R. Nandhini Abirami, P. M. Durai Raj Vincent, Kathiravan Srinivasan, Usman Tariq, Chuan-Yu Chang

“…The survey explores various deep learning techniques adapted to solve computer vision problems using deep convolutional neural networks and deep generative adversarial networks. …”
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Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

“…To overcome these limitations, this study proposes a multi-level feature aggregation and context enhancement network (MACE-Net). The network architecture integrates the GOLD-YOLO module, an advanced object detection approach, alongside the updated deformable convolutional networks (DCNv3). …”
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End-to-End CNN conceptual model for a biometric authentication mechanism for ATM machines by Karthikeyan Velayuthapandian, Natchiyar Murugan, Saranya Paramasivan

“…The proposed method relies on face biometrics, which offers a novel technique to address the current challenge. This article presents a novel end-to-end multiscale attention-based light-weighted deep convolutional neural network (MA-LW-DCNN) framework for enhancing the accuracy of recognizing faces. …”
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HUMAN EMOTION RECOGNITION SYSTEM USING DEEP LEARNING ALGORITHMS by Kateryna Yuvchenko, Valentyn Yesilevskyi, Olena Sereda

“…An image classification method based on a densely connected convolutional neural network is also used. Results: the results of this work showed that the method of image classification, based on a densely connected convolutional neural network, is well suited for solving the problems of emotion recognition, because it has a fairly high accuracy. …”
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Conceptual Approach to Permanent Magnet Synchronous Motor Turn-to-Turn Short Circuit and Uniform Demagnetization Fault Diagnosis by Yinquan Yu, Chun Yuan, Dequan Zeng, Giuseppe Carbone, Yiming Hu, Jinwen Yang

“…Permanent magnet synchronous motors (PMSMs) play a crucial role in industrial production, and in response to the problem of PMSM turn-to-turn short-circuit and demagnetization faults affecting production safety, this paper proposes a PMSM turn-to-turn short-circuit and demagnetization fault diagnostic method based on a convolutional neural network and bidirectional long and short-term memory neural network (CNN-BiLSTM). …”
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Review of Research on Trajectory Prediction of Road Pedestrian Behavior by YANG Zhiyong, GUO Jieru, GUO Zihang, ZHANG Ruixiang, ZHOU Yu

“…Special emphasis is placed on deep learning methods, categorized by network architecture into sequential models, convolutional neural networks, graph convolutional networks,  generative adversarial networks, etc. …”
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Research on geomagnetic indoor high-precision positioning algorithm based on generative model by Shuai MA, Ke PEI, Huayan QI, Hang LI, Wen CAO, Hongmei WANG, Hailiang XIONG, Shiyin LI

“…Aiming at the current bottleneck of constructing a fine geomagnetic fingerprint library that required a lot of labor costs, two generative models called the conditional variational autoencoder and the conditional confrontational generative network were proposed, which could collect a small number of data samples for a given location, and generate pseudo-label fingerprints.At the same time, in order to solve the problem of low positioning accuracy of single-point geomagnetic fingerprints, a geomagnetic sequence positioning algorithm based on attention mechanism of convolutional neural network-gated recurrent unit was designed, which could effectively use the spatial and temporal characteristics of fingerprints to achieve precise positioning.In addition, a real-time, portable mobile terminal data collection and positioning system was also designed and built.The actual test shows that the proposed model can effectively construct the available geomagnetic fingerprint database, and the average error of the proposed algorithm can reach 0.16 m.…”
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A Study on the Construction of Translation Curriculum System for English Majors from the Perspective of Human-Computer Interaction by Qi Li

“…Then, the enhanced data is fed into a graph convolutional neural network for node feature extraction to obtain node representations of users and items. …”
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4D trajectory lightweight prediction algorithm based on knowledge distillation technique by Weizhen Tang, Jie Dai, Zhousheng Huang, Boyang Hao, Weizheng Xie

“…The student network adopts a Temporal Convolutional Network–LSTM (TCN–LSTM) design, integrating dilated causal convolutions and two LSTM layers for efficient temporal modeling. …”
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A novel lightweight deep learning framework using enhanced pelican optimization for efficient cyberattack detection in the Internet of Things environments by Yaozhi Chen, Yan Guo, Yun Gao, Baozhong Liu

“…To counter these challenges, the current study proposes a hybrid model incorporating an efficient convolutional neural network (CNN) and an enhanced pelican optimization algorithm (EPOA) to detect IoT network attacks. …”
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Grinding wheel wear evaluation with the PMSCNN model by Sumei Si, Zekai Si, Deqiang Mu, Hailiang Tang

“…Consequently, the grinding wheel wear assessment model PMSCNN derived from the Convolutional Neural Network (CNN) and the Transformer model is presented. …”
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Ulcerative Severity Estimation Based on Advanced CNN–Transformer Hybrid Models by Boying Nie, Gaofeng Zhang

“…This study aims to apply a state-of-the-art hybrid neural network architecture—combining convolutional neural networks (CNNs) and transformer models—to classify intestinal endoscopy images, utilizing the largest publicly available annotated UC dataset. …”
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LE-YOLO: A Lightweight and Enhanced Algorithm for Detecting Surface Defects on Particleboard by Chao He, Yongkang Kang, Anning Ding, Wei Jia, Huaqiong Duo

“…To address these challenges, this study proposes the LE-YOLO model, which incorporates a normalized Wasserstein distance into the loss function to enhance the detection capability for minute surface defects. A dynamic mixed convolutional network module is introduced to construct a lightweight backbone architecture. …”
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Lightweight and efficient skeleton-based sports activity recognition with ASTM-Net. by Bin Wu, Mei Xue, Ying Jia, Ning Zhang, GuoJin Zhao, XiuPing Wang, Chunlei Zhang

“…Skeletal data has emerged as a robust modality for HAR, overcoming challenges such as noisy backgrounds and lighting variations. However, current Graph Convolutional Network (GCNN)-based methods for skeletal activity recognition face two key limitations: (1) they fail to capture dynamic changes in node affinities induced by movements, and (2) they overlook the interplay between spatial and temporal information critical for recognizing complex actions. …”
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TCBGY net for enhanced wear particle detection in ferrography using self attention and multi scale fusion by Lei He, Haijun Wei, Cunxun Sun

“…Secondly, we introduce the convolutional block attention module (CBAM) into the neck network to enhance salience for detecting wear particles while suppressing irrelevant information interference. …”
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A Configurable Accelerator for CNN-Based Remote Sensing Object Detection on FPGAs by Yingzhao Shao, Jincheng Shang, Yunsong Li, Yueli Ding, Mingming Zhang, Ke Ren, Yang Liu

“…Convolutional neural networks (CNNs) have been widely used in satellite remote sensing. …”
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Inter-turn Short-circuit Fault Diagnosis and Severity Estimation for Five-phase PMSM by Yijia Huang, Wentao Huang, Tinglong Pan, Dezhi Xu

“…In this article, an inter-turn short-circuit (ITSC) fault diagnosis and severity estimation method based on extended state observer (ESO) and convolutional neural network (CNN) is proposed for five-phase permanent magnet synchronous motor (PMSM) drives. …”
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Roughness prediction of end milling surface for behavior mapping of digital twined machine tools [version 2; peer review: 2 approved, 1 approved with reservations] by Gedong Jiang, Suiyan Shang, Wenwen Tian, Zheng Sun, Jun Xu, Dawei Zhang, Chi Fai Cheung

“…Methods The proposed model applies a three-layer backpropagation neural network by using real-time vibration, force, and current sensor data collected during the end milling machining process. …”
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