A Novel CNN-Based Framework for Detection and Classification of Power Quality Disturbances: Exploring Multi-Class Versus Multi-Label Classification by Aleksandra Zlatkova, Dimitar Taskovski

“…The performance of the model was rigorously evaluated using various metrics across different scenarios, which demonstrated exceptional accuracy and robustness. …”
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Individual Contribution-Based Spatial-Temporal Attention on Skeleton Sequences for Human Interaction Recognition by Xing Liu, Bo Gao

“…First, variations in camera positions and viewpoints can cause significant differences in skeletal data for actions of the same type. …”
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Tissue Puncture Event Detection in Needle Procedures using Vibroacoustic Signals - ResNet optimised Phantom Results by Serwatka Witold, Rzepka Dominik, Oran Hamza, Steeg Katharina, Krombach Gabriele, Stefanski Juliusz, Heryan Katarzyna, Friebe Michael

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Integrated CNN‐LSTM for Photovoltaic Power Prediction based on Spatio‐Temporal Feature Fusion by Junwei Ma, Meiru Huo, Jinfeng Han, Yunfeng Liu, Shunfa Lu, Xiaokun Yu

“…Additionally, we designed different case studies to compare model performance under sunny, rainy, and cloudy conditions. …”
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Multi-Harmonic Nonlinear Ultrasonic Fusion with Deep Learning for Subtle Parameter Identification of Micro-Crack Groups by Qi Lin, Xiaoyang Bi, Xiangyan Ding, Bo Yang, Bingxi Liu, Xiao Yang, Jie Xue, Mingxi Deng, Ning Hu

“…First, we trained a one-dimensional convolutional neural network (1D CNN) with various time-domain signals obtained from finite element method (FEM) models and analyzed the sensitivity of different harmonic nonlinear responses to various subtle parameters of micro-crack groups. …”
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Node Classification Based on Kolmogorov-Arnold Networks by YUAN Lining, FENG Wengang, LIU Zhao

“…In the node classification task, G-KAN outperforms the currently advanced baselines and raises Micro-F1 and Macro-F1 by 50.42 and 52.84 percentage points respectively compared with graph convolutional networks (GCN) on BlogCatalog. In activation comparison experiments, the method introduced by KAN outperforms the variants that use different activation functions and demonstrates stronger generalization across various datasets. …”
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Classifying sex with volume-matched brain MRI by Matthis Ebel, Martin Domin, Nicola Neumann, Carsten Oliver Schmidt, Martin Lotze, Mario Stanke

“…Sex differences in the size of specific brain structures have been extensively studied, but careful and reproducible statistical hypothesis testing to identify them produced overall small effect sizes and differences in brains of males and females. …”
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Automatic segmentation and volume measurement of anterior visual pathway in brain 3D-T1WI using deep learning by Yongliang Han, Haixiang Wang, Qi Luo, Jingjie Wang, Chun Zeng, Qiao Zheng, Linquan Dai, Yiqiu Wei, Qiyuan Zhu, Wenlong Lin, Shaoguo Cui, Yongmei Li

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A study on Chinese language Cross-Modal pedestrian image information retrieval by Yan Xie, Jian Qu

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Research on Predictive Analysis Method of Building Energy Consumption Based on TCN-BiGru-Attention by Sijia Fu, Rui Zhu, Feiyang Yu

“…Although there are currently a large number of energy consumption research methods, each method has different applicability and advantages and disadvantages. …”
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Ignition delay prediction for fuels with diverse molecular structures using transfer learning-based neural networks by Mo Yang, Dezhi Zhou

“…A comprehensive dataset of ignition delays was generated using a random sampling technique across different temperatures and pressures, focusing on hydrocarbon fuels with 1–4 carbon atoms. …”
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Dual-Channel CNN-Based Framework for Automated Rebar Detection in GPR Data of Concrete Bridge Decks by Sepehr Pashoutani, Mohammadsajjad Roudsari, Jinying Zhu

“…This paper presents two automated rebar detection algorithms based on Convolutional Neural Network (CNN) machine learning techniques. …”
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Efficient Pruning of Detection Transformer in Remote Sensing Using Ant Colony Evolutionary Pruning by Hailin Su, Haijiang Sun, Yongxian Zhao

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A comparative analysis of deep learning models for accurate spatio-temporal soil moisture prediction by Litao Zhu, Wen Dai, Jiru Huang, Zicong Luo

“…The performance was analyzed by different accuracy metrics. The results show that ConvLSTM has the lowest errors in both time series and spatio-temporal prediction. …”
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On the Question of the Applicability of Artificial Intelligence Systems to Forensic Examination of Documents and Their Requisites by A. F. Kupin, A. S. Kovalenko

“…The procedure and principles of operation of convolutional neural networks are described and, using their example, the results that can be achieved during forensic handwriting and technical forensic examinations of documents, as well as studies conducted within the framework of forensic expert activities, in particular, the identification of signs of technical forgery of documents (installation, erasure, additions, finishing) are indicated, establishing the facts of the execution of several signatures or handwritten records by one or different performers, establishing the original content of the records, fragments of which have been partially lost or distorted. …”
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Multi-branch network for double JPEG detection and localization by Ahmed M. Fouad, Hala H. Zayed, Ahmed Taha

“…JPEG image tampering often involves recompression with a different quantization table, known as double JPEG compression. …”
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Global information aware network with global interaction graph attention for infrared small target detection by Ruimin Yang, Yidan Zhang, Guangshuai Gao, Liang Liao, Chunlei Li

“…Additionally, the multi‐scale context fusion module utilises self‐attention and dilation convolution to complement richer feature details at different scales. …”
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An Attention-Based Spatial-Spectral Joint Network for Maize Hyperspectral Images Disease Detection by Jindai Liu, Fengshuang Liu, Jun Fu

“…Experimental results demonstrate the effectiveness of the proposed model across different field scenarios, achieving overall accuracies (OAs) of 99.24% and 97.4% on close-up hyperspectral images and middle-shot hyperspectral images, respectively. …”
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Deep Learning Techniques for Detecting Morphed Face Images: A Literature Review by Pedro Morais, Ines Domingues, Jorge Bernardino

“…These models have shown considerable potential in automating feature extraction, identifying subtle manipulation traces, and improving detection accuracy across different morphing techniques. However, as morphing techniques continue to evolve and produce more sophisticated attacks, current methods face challenges in detecting subtle artifacts, particularly in high-quality morphs. …”
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Enhancing Medical Image Classification with Unified Model Agnostic Computation and Explainable AI by Elie Neghawi, Yan Liu

“…By unifying and standardizing computational models and algorithms, UMAC ensures adaptability across different data types and computational environments while incorporating state-of-the-art methodologies. …”
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