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. …”
Get full text

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

Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Performance improvement of extreme multi-label classification using K-way tree construction with parallel clustering algorithm by Purvi Prajapati, Amit Thakkar

“…eXtreme Multi-Label Classification (XMLC) is the particular case of Multi-Label Classification, which deals with an extremely high number of labels. …”
Get full text

Klasifikasi Penyakit pada Tanaman Berdasarkan Citra Daun Menggunakan Metode Convolutional Neural Network by Denis Aji Pangestu, Okta Qomaruddin Aziz, Cahyo Crysdian

“…This study demonstrates that the CNN method is effective in plant disease classification, with optimal performance at an 80:20 data ratio and single-stage classification. …”
Get full text

THE PRINCIPLES AND POSSIBILITIES OF FORECASTING: THE PAYABLES AND RECEIVABLES BALANCE SETTLEMENTS by T. P. Karpova, V. V. Karpova

“…The latter has an information and analytical function preparing the basis for financial strategy development and observance of the contractual discipline in combination with an adopted accounting policy. The urgency of the issues concerning the effective management of receivables and payables is growing higher because of the continuing process of payment discipline violation and this process is very difficult to manage. …”
Get full text

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. …”
Get full text

Joint feature selection and classification of low-resolution satellite images using the SAT-6 dataset by Rajalaxmi Padhy, Sanjit Kumar Dash, Jibitesh Mishra

“…In summary, this paper provides compelling evidence that this RankEnsembleFS methodology presents excellent performance and overcomes key issues in feature selection and image classification for the SAT-6 dataset.…”
Get full text

Intracranial hemorrhage segmentation and classification framework in computer tomography images using deep learning techniques by S. Nafees Ahmed, P. Prakasam

“…In this paper, MUNet (Multiclass-UNet) based Intracranial Hemorrhage Segmentation and Classification Framework (IHSNet) is proposed to successfully segment multiple kinds of hemorrhages while the fully connected layers help in classifying the type of hemorrhages.The segmentation accuracy rates for hemorrhages are 98.53% with classification accuracy stands at 98.71% when using the suggested approach. …”
Get full text

Incorporating Crowdsourced Annotator Distributions into Ensemble Modeling to Improve Classification Trustworthiness for Ancient Greek Papyri by Graham West, Matthew I. Swindall, Ben Keener, Timothy Player, Alex C. Williams, James H. Brusuelas, John F. Wallin

“…Performing classification on noisy, crowdsourced image datasets can prove challenging even for the best neural networks. …”
Get full text

Class-Balanced Random Patch Training to Address Class Imbalance in Tiling-Based Farmland Classification by Yeongung Bae, Yuseok Ban

“…However, typical tiling-based classification approaches, which extract patches at fixed offsets within each image during training, often suffer from structural issues such as patch duplication, limiting training diversity. …”
Get full text

Critical Review on Powertrain Technologies for Electric Vehicles: Classification, Broadly Adopted Topologies, and Future Challenges by Sadeq Ali Qasem Mohammed, Samer Saleh Hakami, Mahmoud Kassas, Mohammad M. Almuhaini

“…However, there are major issues that may complicate the adoption of EVs including battery limitations, energy density, charging speed, insufficient charging stations, cost, and reliance on critical materials for instance, lithium and cobalt. …”
Get full text

Convolutional Neural Network Based Vehicle Classification in Adverse Illuminous Conditions for Intelligent Transportation Systems by Muhammad Atif Butt, Asad Masood Khattak, Sarmad Shafique, Bashir Hayat, Saima Abid, Ki-Il Kim, Muhammad Waqas Ayub, Ahthasham Sajid, Awais Adnan

“…Deep learning-based classification systems have been proposed to incorporate the above-mentioned issues in traditional methods. …”
Get full text

Text classification using SVD, BERT, and GRU optimized by improved Seagull optimization (ISO) algorithm by Yuanyuan Chen, Nan Sun, Yuanbang Li, Rong Peng, Abbas Habibi

“…In the present research, a Gated Recurrent Unit (GRU) optimized by the Improved Seagull Optimization (ISO) algorithm was utilized to address these issues, resulting in notable improvements in classification performance. …”
Get full text

Classification of heart diseases using time-frequency representations of electrocardiogram signals by transfer learning networks by Amir Hossein Jalalzadeh, Hamid Ebrahimi, Maryam Jahangiri Moghadam

Get full text

A new locally adaptive K-nearest centroid neighbor classification based on the average distance by Benqiang Wang, Shunxiang Zhang

“…To address these three issues, we propose a new locally adaptive k-nearest centroid neighbour classification based on the average distance (AD-LAKNCN) in this paper. …”
Get full text

Research on Food Image Classification Algorithm based on Improved MobileNetV3-Large by HE Wei-chan, YANG Zhi-jing, QIN Jing-hui

“…In order to address these issues, this paper proposed a food image classification algorithm based on improved MobileNetV3-Large. …”
Get full text

Condition monitoring and multi-fault classification of hydraulic systems using multivariate functional data analysis by Cevahir Yildirim, Alba M. Franco-Pereira, Rosa E. Lillo

“…The proposed method systematically tackles condition-based diagnostics and addresses fundamental issues in multi-fault classification. Experimental results demonstrate that this approach achieves high classification accuracy using raw multi-sensor data, establishing multivariate FDA as a powerful tool for fault diagnosis in complex systems.…”
Get full text