FFTL-Net: a network for the classification of skin diseases based on feature fusion and transfer learning by Xiaowei Song, Yurong Mei, Zhilei Zhao, Hao Chang, Lina Han, Hui Wang, Xinyi Zhang, Guoqiang Wang

“…The objective is to address the issues of data imbalance, overfitting, and inadequate generalization ability in skin disease datasets and recognition models. …”
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Privacy-enhanced skin disease classification: integrating federated learning in an IoT-enabled edge computing by Nada Alasbali, Jawad Ahmad, Ali Akbar Siddique, Oumaima Saidani, Alanoud Al Mazroa, Asif Raza, Rahmat Ullah, Muhammad Shahbaz Khan

“…Most existing automated detection/classification approaches that utilize machine learning or deep learning poses privacy issues, as they involve centralized computing and require local storage for data training.MethodsKeeping the privacy of sensitive patient data as a primary objective, in addition to ensuring accuracy and efficiency, this paper presents an algorithm that integrates Federated learning techniques into an IoT-based edge-computing environment. …”
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DSGAU: Dual-Scale Graph Attention U-Nets for Hyperspectral Image Classification With Limited Samples by Hongzhuang Ji, Leying Song, Zhaohui Xue, Hongjun Su

“…Nevertheless, prevalent graph pooling techniques often employ single-scale strategies that inadequately capture multiscale features, potentially leading to information loss or redundancy. To address this issue, we propose a dual-scale graph attention U-Nets for HSI classification with limited samples. …”
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GLN-LRF: global learning network based on large receptive fields for hyperspectral image classification by Mengyun Dai, Tianzhe Liu, Youzhuang Lin, Zhengyu Wang, Yaohai Lin, Changcai Yang, Riqing Chen

“…Such locality-based methods have limitations in capturing global contextual information and incur high computational costs due to patch overlap. To alleviate these issues, we propose a global learning network with a large receptive fields network (GLNet) to capture more comprehensive and accurate global contextual information, thereby enriching the underlying feature representation for hyperspectral image classification. …”
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Encoding-Based Machine Learning Approach for Health Status Classification and Remote Monitoring of Cardiac Patients by Sohaib R. Awad, Faris S. Alghareb

“…In this context, developing a GUI-based classification approach can significantly facilitate online monitoring and provide real-time warnings by predicting potential complications. …”
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GAN-enhanced deep learning for improved Alzheimer's disease classification and longitudinal brain change analysis by Purushottam Pandey, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Jyoti Pruthi, Eid Albalawi, Ali Algarni, Ahlam Almusharraf

“…However, despite these advancements, issues such as limited accuracy, computational complexity, and the risk of overfitting still pose challenges in the field of AD classification. …”
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Representation Learning of Multi-Spectral Earth Observation Time Series and Evaluation for Crop Type Classification by Andrea González-Ramírez, Clement Atzberger, Deni Torres-Roman, Josué López

“…Important monitoring tasks include land use and land cover classification, change detection, forest monitoring and crop type identification, among others. …”
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Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

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A reduced dimension multiple signal classification–based direct location algorithm with dense arrays by Jianfeng Li, Gaofeng Zhao, Baobao Li, Xianpeng Wang, Mengxing Huang

“…Aiming at the issue of parameter matching in conventional two-step location, a reduced dimension multiple signal classification direct position determination algorithm based on multi-array is proposed. …”
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Sleep-related breathing disorders in patients with heart failure: classification, epidemiology and pathophysiology. Part I by K. S. Krupichka, M. V. Agaltsov, R. P. Myasnikov, O. M. Drapkina

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Mental Health Classification Using Machine Learning with PCA and Logistics Regression Approaches for Decision Making by Hendra Hendra, Mustafa Mat Deris, Ika Safitri Windiarti

“…Research on mental health classification using machine learning techniques, particularly PCA and logistic regression, is significant because it has the potential to improve decision-making in mental health care.…”
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AdaPDTW: An Efficient Abstract-Adaptive Piecewise Dynamic Time Warping for Time Series Classification by Qinglin Cai, Leiying Chen, Jian Shao, Ling Chen

“…Dynamic Time Warping (DTW) offers precise similarity measure but suffers from high computational cost. To address this issue, we propose an abstract-adaptive PAR-DTW, which computes DTW in a low-dimensional piecewise abstract representation (PAR) space. …”
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Zero-shot classification with multi-model information interaction and its application in Mars exploration scenarios by TAN Xiaomeng, XI Bobo, XUE Changbin, LI Yunsong

“…To address the issue that traditional Mars image classification methods based on images do not perform well in the face of the complex and unknown environment of Mars and the frequent occurrence of unseen categories, a zero-shot classification algorithm of multi-modal information interaction was studied and the migration and optimization of the algorithm to the field of deep space exploration was explored. …”
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Detection and Classification of Abnormal Power Load Data by Combining One-Hot Encoding and GAN–Transformer by Ting Yang, Hongyi Yu, Danhong Lu, Shengkui Bai, Yan Li, Wenyao Fan, Ketian Liu

“…Furthermore, it outperforms traditional methods such as LSTM-NDT, Transformer, OmniAnomaly and MAD-GAN in Overall Accuracy, Average Accuracy, and Kappa coefficient, thereby validating the effectiveness and superiority of the proposed anomaly detection and classification method.…”
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Enhancing Anti-Money Laundering Frameworks: An Application of Graph Neural Networks in Cryptocurrency Transaction Classification by Stefano Ferretti, Gabriele D'Angelo, Vittorio Ghini

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Integrated Use of Statistical-Based Approaches and Computational Intelligence Techniques for Tumors Classification Using Microarray by Chia-Ding Hou, Yuehjen E. Shao

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Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…Extreme Gradient Boosting (XGBoost) overcomes the issue of overfitting in decision trees by integrating multiple tree models. …”
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Updating TCGA glioma classification through integration of molecular data following the latest WHO guidelines by Mónica Leiria de Mendonça, Roberta Coletti, Céline S. Gonçalves, Eduarda P. Martins, Bruno M. Costa, Susana Vinga, Marta B. Lopes

“…To address this issue, we propose two methods for updating the tumor classification of TCGA glioma samples according to the 2016 and 2021 WHO guidelines, through the integration of open-access curated molecular profiling data. …”
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Malaria Cell Image Classification Using Compact Deep Learning Architectures on Jetson TX2 by Adán-Antonio Alonso-Ramírez, Alejandro-Israel Barranco-Gutiérrez, Iris-Iddaly Méndez-Gurrola, Marcos Gutiérrez-López, Juan Prado-Olivarez, Francisco-Javier Pérez-Pinal, J. Jesús Villegas-Saucillo, Jorge-Alberto García-Muñoz, Carlos-Hugo García-Capulín

“…Malaria is a significant global health issue, especially in tropical regions. Accurate and rapid diagnosis is critical for effective treatment and reducing mortality rates. …”
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Biopreservation of Food Using Bacteriocins From Lactic Acid Bacteria: Classification, Mechanisms, and Commercial Applications by Dhea Alya Putri, Jiang Lei, Nia Rossiana, Yolani Syaputri

“…Moreover, spoilage bacteria in food can be pathogenic, leading to foodborne disease that endangers human health. This issue has also driven the widespread use of synthetic preservatives, which have negative effects both in the short and long term. …”
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