A feature enhancement FCOS algorithm for dynamic traffic object detection by Tuqiang Zhou, Wei Liu, Haoran Li

“…First, the dynamic convolution module was designed in the backbone network to identify different object features to the maximum extent. …”
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Research on Unsupervised Domain Adaptive Bearing Fault Diagnosis Method Based on Migration Learning Using MSACNN-IJMMD-DANN by Xiaoxu Li, Jiahao Wang, Jianqiang Wang, Jixuan Wang, Qinghua Li, Xuelian Yu, Jiaming Chen

“…To address the problems of feature extraction, cost of obtaining labeled samples, and large differences in domain distribution in bearing fault diagnosis on variable operating conditions, an unsupervised domain-adaptive bearing fault diagnosis method based on migration learning using MSACNN-IJMMD-DANN (multi-scale and attention-based convolutional neural network, MSACNN, improved joint maximum mean discrepancy, IJMMD, domain adversarial neural network, DANN) is proposed. …”
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High precision light field image depth estimation via multi‐region attention enhanced network by Jie Li, Wenxuan Yang, Chuanlun Zhang, Heng Li, Xinjia Li, Lin Wang, Yanling Wang, Xiaoyan Wang

“…Firstly, we construct a multi‐region disparity selection module based on angular patch, which selects specific regions for generating angular patch, achieving representative sub‐angular patch by balancing different regions. Secondly, different from traditional guided deformable convolution, the guided optimisation leverages colour prior information to learn the aggregation of sampling points, which enhances the deformable convolution ability by learning deformation parameters and fitting irregular windows. …”
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Action Recognition with 3D Residual Attention and Cross Entropy by Yuhao Ouyang, Xiangqian Li

“…Simultaneously, we used the cross-entropy loss function to describe the difference between the predicted value and GT to guide the model’s backpropagation. …”
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Comparative analysis of data transformation methods for detecting non-technical losses in electricity grids by Maria Gabriel Chuwa, Daniel Ngondya, Rukia Mwifunyi

“…Six encoding techniques for time series data were evaluated: Markov transition fields (MTF), Gramian angular summation field (GASF), Gramian angular difference field (GADF), Recurrence plots (RP), and time–frequency analysis methods, including short-time Fourier transform (STFT) and continuous wavelet transform (CWT). …”
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DSNET: A Lightweight Segmentation Model for Segmentation of Skin Cancer Lesion Regions by Yucong Chen, Guang Yang, Xiaohua Dong, Junying Zeng, Chuanbo Qin

“…To reduce the model size and guarantee model segmentation performance, we proposed a detail-enhanced separable difference convolution as a base module in the model. …”
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YOLO-EFM: Efficient traffic flow monitoring algorithm with enhanced multi-level information fusion by Shizhou Xu, Kaidi Cui

“…The study establishes a generalized efficient layer aggregation network incorporating Sobel convolution and develops a novel feature focus module that effectively aggregates information from different feature map levels. …”
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Vision-based detection algorithm for monitoring dynamic change of fire progression by Yongyoon Suh

“…This study aims to define vision-based patterns of fire events to identify multiple objects that contribute to different types of fire accidents. To achieve this, a convolutional neural network (CNN) based on deep learning is applied to detect fire events through vision-based patterns. …”
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A Closed-loop Detection Algorithm Based on Dynamic Time Warping by ZHU Tian, PENG Zhichuan, ZHANG Zhiteng, ZHU Zemin, XIE Yongbo, WANG Wenming

“…Considering the influence of matching sequence length on the experimental results, the quasi-call curves and ROC curves obtained under different sequence lengths are compared in detail to determine the most suitable matching sequence length. …”
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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

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Calculus accumulation-based method for extracting values of instrumentation image by Dianming Wang, Li Zhou, Xiangxin Chen, Mingxin Yi, Xiaoju Yin

“…Through the experimental comparison and analysis of outdoor dust occlusion, droplet occlusion, leaf occlusion, and different lighting conditions, the results show that the algorithm has good robustness, is almost not disturbed by the external environment, and has high recognition accuracy. …”
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Prediction and classification of wheat plant disease in Pakistan using deep learning techniques by Muhammad Usman Malik, Muhammad Faisal Hayat

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RS-SCBiGRU: a noise-robust neural network for high-speed motor fault diagnosis with limited samples by Sun Fenghao, Li Guofa, He Jialong, Liu Shaoyang

“…Furthermore, to enhance the richness of feature representations and strengthen information exchange between different feature channels, this paper proposes a frequency-adaptive convolutional layer (SCNET), which significantly optimizes the performance of Bidirectional Gated Recurrent Units (BiGRU) in fault feature extraction. …”
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Optimizing AlexNet for accurate tree species classification via multi-branch architecture and mixed-domain attention by Jianjianxian Liu, Tao Xing, Xiangyu Wang

“…The multi-branch convolutional module extracts diverse features by processing input with branches of different kernel sizes, capturing both fine and global details. …”
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Deep CNN ResNet-18 based model with attention and transfer learning for Alzheimer's disease detection by Sofia Biju Francis, Sofia Biju Francis, Jai Prakash Verma

“…Additionally, pre-trained ResNet-18 models were created with and without the SE block to compare ROC and accuracy values across different hyperparameters.ResultsThe proposed model achieved ROC values of 95% for Alzheimer's Disease (AD), 95% for Cognitively Normal (CN), and 93% for Mild Cognitive Impairment (MCI), with a maximum test accuracy of 88.51%. …”
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Building Surface Defect Detection Based on Improved YOLOv8 by Xiaoxia Lin, Yingzhou Meng, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Weihao Gong, Xinyue Xiao

“…The dataset used in this study contains six common building surface defects, and the images are captured in diverse scenarios with different lighting conditions, building structures, and ages of material. …”
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Aerial Biological Target Classification Based on Time–Frequency Multi-Scale Feature Fusion Network by Lianjun Wang, Rui Wang, Weidong Li, Jiangtao Wang, Yujia Yan, Cheng Hu

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Rapid diagnosis of rheumatoid arthritis and ankylosing spondylitis based on Fourier transform infrared spectroscopy and deep learning by Wei Shuai, Xue Wu, Chen Chen, Enguang Zuo, Xiaomei Chen, Zhengfang Li, Xiaoyi Lv, Lijun Wu, Cheng Chen

“…Three multi-scale convolutional modules with different specifications were designed based on the multi-scale convolutional neural network (MSCNN) to effectively fuse the local features to enhance the generalization ability of the model. …”
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A depth-wise separable VGG19-capsule network for enhanced bell pepper and grape leaf disease classification with ensemble activation by Midhun P Mathew, Sudheep Elayidom, Jagathy Raj V P, Abubeker K M

“…The novel contribution lies in the enhanced VGG19 architecture, incorporating depth-wise separable convolution, batch normalization, and a 40% dropout by introducing convolutional layers before the primary capsule layer. …”
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Mechanical Fault Diagnosis Method of a Disconnector Based on Improved Dung Beetle Optimizer–Multivariate Variational Mode Decomposition and Convolutional Neural Network–Bidirection... by Chi Zhang, Hongzhong Ma, Wei Sun

“…The verification of the experimental data shows that the proposed algorithm can successfully diagnose different mechanical faults of the disconnector, and the accuracy rate was 96.67%. …”
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