Nature-inspired MPPT algorithms for solar PV and fault classification using deep learning techniques by S. Senthilkumar, V. Mohan, S. P. Mangaiyarkarasi, R. Gandhi Raj, K. Kalaivani, N. Kopperundevi, M. Chinnadurai, M. Nuthal Srinivasan, L. Ramachandran

“…Among all, CNN provides a maximum accuracy of 94.11% in fault classification. Simulation analysis demonstrates the proof-of-concept for maximum TE and classification accuracy for all the methods. …”
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An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification by Ayesha Shaik, Shivanya Shomir Dutta, Ishaan Milind Sawant, Shreyas Kumar, Ananthakrishnan Balasundaram, Kanjar De

“…Abstract Skin lesions remain a significant global health issue, with their incidence rising steadily over the past few years. …”
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Hierarchical 2-D/3-D Object-Based Classification of Photogrammetric Textured Mesh Models by Zhongwen Hu, Jinhua Zhang, Zhigang Liu, Yinghui Zhang, Jingzhe Wang, Qian Zhang, Guofeng Wu

“…To address this issue, we propose a hierarchical object-based method for the classification of TMMs, consisting of three key steps: 1) the TMM is first hierarchically segmented into ground surface meshes and off-ground 3-D objects using a cloth-simulated filtering algorithm; 2) the ground surface mesh is projected to 2-D ortho-image, where object-based image classification is used to classify pixels. …”
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SSTMNet: Spectral-Spatio-Temporal and Multiscale Deep Network for EEG-Based Motor Imagery Classification by Albandari Alotaibi, Muhammad Hussain, Hatim Aboalsamh

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Application and Analysis of Random Forest and Support Vector Classification in Risk Prediction of Childhood Obesity and Hyperuricemia by Wang Y, Shi S, Wei X, Wu Y, Shi Y, Cai J

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A Novel Two-Stream Network for Few-Shot Remote Sensing Image Scene Classification by Yaolin Lei, Yangyang Li, Heting Mao

“…Recently, remote sensing image scene classification (RSISC) has gained considerable interest from the research community. …”
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Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China by Jie Xue, Xianglin Zhang, Songchao Chen, Bifeng Hu, Nan Wang, Zhou Shi

“…Despite the differences in LULC classification schemes, there is a lack of research on assessing the accuracy of their application to croplands in a unified framework. …”
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Issues of National Drug Security in Formation of a Reserve of Antibacterial Agents Intended to Eliminate Medical and Sanitary Consequences of Emergencies by L. Yu. Chernikova, V. N. Dmitruk, N. L. Denisov, E. G. Morozova, A. V. Ratkin, E. V. Karakulova

“…The article considers the issues of forming a reserve of antibacterial agents designed to eliminate medical and sanitary consequences of emergencies from the perspective of national drug security.Aim. …”
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Design Guidelines for Combining Digital Human Modeling and Virtual Reality to Foresee Workplaces Ergonomics Issues During Product Development by Adailton G. Silva, Rafael Vieira Miguez, Lucas G. G. de Almeida, Márcio F. Catapan, Carina S. Silveira, Marcelo da S. Hounsell, Marcus V. M. Gomes, Ingrid Winkler

“…Based on physical observations of body-posture angles and total effort classification, our proof of concept performed comparably to conventional methods. …”
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Development and validation of a deep learning image quality feedback system for infant fundus photography by Helei Wang, Longhui Li, Wenjuan Wang, Zhiwen Li, Tianzi Jian, Xueying Yang, Boxuan Song, Shiqiang Li, Fabao Xu, Shaopeng Liu, Ying Li

“…The area under the curve (AUC) values for discriminating poor quality, adequate quality, and excellent quality images in the external validation dataset were 0.802, 0.691, and 0.926, respectively. For most classification tasks related to identifying issues in adequate and poor quality images, the AUC values consistently exceeded 0.8. …”
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Challenges in developing a digital pathology consultation network: insights from the MELCAYA experience by Dario Di Gangi, Roberta Gugliotta, Filippo Ugolini, Anna Szumera-Ciećkiewicz, Llucia Alos, Natalia Castrejón, Stephan Forchhammer, Barbara Valeri, Nicolas Macagno, Sule Ozturk Sari, Ozge Hurdogan, Sokol Sina, Sylvie Fraitag, Valerio Gaetano Vellone, Chiara Trambaiolo, Rita Alaggio, Sabrina Rossi, Giovanni Arcuri, Daniela Massi, Claudio Conti

“…Twenty-four cases (11.5 %) exhibited major discordances on melanoma vs atypical melanocytic lesions classification, underscoring the importance of centralized pathological review. …”
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A Frequency-Shifting Variational Mode Decomposition-Based Approach to MI-EEG Signal Classification for BCIs by Haiqin Xu, Shahzada Ali Hassan, Waseem Haider, Youchao Sun, Xiaojun Yu

“…However, traditional signal decomposition (SD) techniques are hindered by two critical issues, mode mixing and mode aliasing, that compromise the quality of the decomposed signal. …”
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SwiftSession: A Novel Incremental and Adaptive Approach to Rapid Traffic Classification by Leveraging Local Features by Tieqi Xi, Qiuhua Zheng, Chuanhui Cheng, Ting Wu, Guojie Xie, Xuebiao Qian, Haochen Ye, Zhenyu Sun

“…However, the increasing prevalence of encrypted traffic and the confidentiality of protocol details have made this task more challenging. To address this issue, we propose a progressive, adaptive traffic classification method called SwiftSession, designed to achieve real-time and accurate classification. …”
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Comparison of CNN Architectures for Pre-Cancerous Cervical Lesion Classification Based on Colposopy Images Using IARC and AnnoCerv Datasets by Sigit Prasetyo Noprianto, Siti Nurmaini, Dian Palupi Rini

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Enhancing heart disease classification with M2MASC and CNN-BiLSTM integration for improved accuracy by Vivek Pandey, Umesh Kumar Lilhore, Ranjan Walia, Roobaea Alroobaea, Majed Alsafyani, Abdullah M. Baqasah, Sultan Algarni

“…To overcome these issues, the research proposed a model for heart disease detection and classification by integrating blockchain technology with a Modified mixed attention-enabled search optimizer-based CNN-Bidirectional Long Short-Term Memory (M2MASC enabled CNN-BiLSTM) model. …”
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Movement Direction Classification Using Low-Resolution ToF Sensor and LSTM-Based Neural Network by Sejik Oh, Kyoung Min Lee, Seok Young Lee, Nam Kyu Kwon

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Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics by Jihan Wang, Zhengxiang Zhang, Yangyang Wang

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DynamicG2B: Dynamic Node Classification with Layered Graph Neural Networks and BiLSTM by Fattah Muhammad Tahabi, Xiao Luo

“…Our evaluation of two benchmark datasets shows that DynamicG2B outperforms seven state-of-the-art baseline models in node classification in dynamic graphs. Additionally, our analysis of attention weights opens up opportunities for further research into exploring the importance of relationships among graph nodes.…”
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Optimizing Parkinson's disease Classification in MRI Scans Using a Modified ResNet50 Architecture by Anuranjani K, Dr. Anitha Karthi

“…Therefore, the ML and DL models are utilized in the classification of MRI scan images, as they face issues in the computations of features through several medical images and classification. …”
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Unsupervised SAR Fine-Grained Ship Classification via Spherical Metric Refinement With Deep Subdomain Adaptation by Zhichao Han, Haitao Lang

“…This article proposes a novel framework, spherical metric refinement with deep subdomain adaptation, to address two crucial issues that are rarely recognized by existing UDA approaches, namely prioritizing <italic>adaptation</italic> over fine-grained <italic>classification</italic> and hindering cross-domain alignment and discrimination due to Euclidean feature norms. …”
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