Radar Emitter Classification Based on a Multiperspective Collaborative Clustering Method and Radar Characteristic Spectrum by Jundi Wang, Xing Wang, Yipeng Zhou, You Chen

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Novel Automatic Classification Method for Geological Structures in Carbonate Formations Based on Electrical Imaging Logging by FU Yafeng, HUANG Ke, ZHU Hanbin, WANG Hui, ZHANG Xu, ZHAO Jie, XIAO Ni

“…In the processing of electrical imaging logging data for carbonate formations, it is challenging to distinguish mudstone laminae, natural fractures, induced fractures, and vugs due to their similar resistivities and overlapping occurrences. To address this issue, this paper proposes an automatic classification method based on skeleton maps and machine learning. …”
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Infrared Thermography-Based Insulator Fault Classification via Unsupervised Clustering and Semi-Supervised Learning by Usman Shafique, Syed Muhammad Alam, Umar Rashid, Wahab Javed, Haris Anwaar, Malik Shah Zeb, Talha Ahmad, Uzair Imtiaz, Frederic Nzanywayingoma

“…This paper addresses the critical issue of insulator fault detection in electric substations, emphasizing the importance of timely identification to prevent accidents. …”
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UN15: An Urban Noise Dataset Coupled with Time–Frequency Attention for Environmental Sound Classification by Yu Shen, Ge Cao, Huan-Yu Dong, Bo Dong, Chang-Myung Lee

“…To address this issue, this study presents two key contributions. …”
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Artificial Intelligence-Based Segmentation and Classification of Plant Images with Missing Parts and Fractal Dimension Estimation by Ganbayar Batchuluun, Seung Gu Kim, Jung Soo Kim, Tahir Mahmood, Kang Ryoung Park

“…However, limited camera viewing angles can cause parts of the plant to be invisible in the acquired images, leading to an inaccurate classification. However, this issue has not been addressed by previous research. …”
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Pseudo-class distribution guided multi-view unsupervised domain adaptation for hyperspectral image classification by Jingpeng Gao, Xiangyu Ji, Geng Chen, Yuhang Huang, Fang Ye

“…However, they all ignore the implicit class distribution information of TD data, which can help the model predict the class with a higher posterior probability. To solve the above issue, we propose pseudo-class distribution guided multi-view unsupervised domain adaptation for hyperspectral image classification (PCDM-UDA). …”
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Comparative Evaluation of Preprocessing Methods for MobileNetV1 and V2 in Waste Classification by Aulia Afifah, Endah Ratna Arumi, Maimunah Maimunah, Setiya Nugroho

“…As tens of millions of tons are produced each year and the management system remains ineffective, environmental conditions and public health continue to deteriorate. To address this issue, it is imperative to develop more accurate and efficient solutions to enhance waste classification and management. …”
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Residual channel attention based sample adaptation few-shot learning for hyperspectral image classification by Yuefeng Zhao, Jingqi Sun, Nannan Hu, Chengmin Zai, Yanwei Han

“…However, existing few-shot methods ignore the correlation between cross-domain feature channels, and the feature representation ability is insufficient. To address above issue, this paper proposes a novel Residual Channel Attention Based Sample Adaptation Few-Shot Learning for Hyperspectral Image Classification(RCASA-FSL) for hyperspectral image classification (HSIC), which can capture and enhance cross-domain dependencies through multi-layer residual connection and random-based feature recalibration. …”
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Structure-guided decoupled contrastive framework for partial multi-view incomplete multi-label classification by Linqian Yang, Tao Zhuang, Xing Jin, Tianyang Cao, Xiyin Wu

“…However, due to the limitations of data collection and the subjectivity of manual labeling, multi-view multi-label learning often faces both partial views and incomplete labels, substantially impacting the performance of existing classification methods in practical applications. Although existing methods have attempted to address this issue, they struggle to fully exploit the consistency and complementarity of multi-view multi-label data simultaneously. …”
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Spiking neural network tactile classification method with faster and more accurate membrane potential representation by Jing Yang, Zukun Yu, Xiaoyang Ji, Zhidong Su, Shaobo Li, Yang Cao

“…However, traditional SNN classification methods often encounter under‐convergence when using membrane potential representation, decreasing their classification accuracy. …”
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A Novel Training Strategy for Deep Learning Model Compression Applied to Automatic Modulation Classification by Mateus A. Goldbarg, Micael Balza, Sergio N. Silva, Lucileide M. D. Silva, Marcelo A. C. Fernandes

“…To tackle this issue, a novel training strategy is proposed in this study. …”
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High-accuracy combustible gas cloud imaging system using YOLO-plume classification network by Jiani Zhou, Yang Liu, Yong Zhang, Haotian Hu, Zenan Leng, Feng Sun, Chen Chen

“…Due to the irregular shape and ambiguous boundary of the gas, traditional motion detection algorithms are difficult to adapt to the changes in the gas movement state with the environment, resulting in an increased probability of false alarms. To address this issue, this paper proposes a gas plume-constrained YOLOv11 model based on infrared imaging detection technology, named YPCN (YOLO-Plume Classification Network). …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

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Classification of melanoma skin Cancer based on Image Data Set using different neural networks by Rukhsar Sabir, Tahir Mehmood

“…Abstract This paper aims to address the pressing issue of melanoma classification by leveraging advanced neural network models, specifically basic Convolutional Neural Networks (CNN), ResNet-18, and EfficientNet-B0. …”
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Sample Denoising and Optimization Technique Based on Noise Filtering and Evolutionary Algorithms for Imbalanced Data Classification by Fhira Nhita, Asniar, Isman Kurniawan, Adiwijaya

“…Imbalanced data remains a challenge in classification research and significantly influences classifier performance. …”
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THE OPTIMIZATION METHOD OF FUZZY AUTOMATIC CLASSIFICATION IN THE PROBLEM OF COMBINING THE ASSESSMENTS OF TRAJECTOR MEASUREMENTS IN THE RADAR SYSTEM by A. V. Khizhniak

“…The paper describes the application of the optimization method of fuzzy automatic classification in the problem of combining estimates of trajectory measurements in a radar system. …”
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Classification of tomato leaf disease using Transductive Long Short-Term Memory with an attention mechanism by Aarthi Chelladurai, D.P. Manoj Kumar, S. S. Askar, Mohamed Abouhawwash, Mohamed Abouhawwash

“…However, effective harvesting still remains a major issue because tomatoes are easily susceptible to weather conditions and other types of attacks. …”
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FUSCANet: Enhancing Skin Disease Classification Through Feature Fusion and Spatial-Channel Attention Mechanisms by Qinyang Liu, Xuan Wang, Hongjiu Liu, Xiangzhen Zang, Lei Li, Zhanlin Ji, Ivan Ganchev

“…Skin diseases represent a prevalent global health issue that significantly impacts the physical and mental well-being of patients. …”
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Machine learning prediction of coal workers’ pneumoconiosis classification based on few-shot clinical data by Jiaqi Jia, Jingying Huang, Yuming Cui, Dekun Zhang, Haiquan Li, Songquan Wang, Wenlu Hang

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