A Novel Deep Learning Model for Motor Imagery Classification in Brain–Computer Interfaces by Wenhui Chen, Shunwu Xu, Qingqing Hu, Yiran Peng, Hong Zhang, Jian Zhang, Zhaowen Chen

“…However, the intricate time–frequency dynamics and inter-channel redundancy of EEG signals remain key challenges, often limiting the effectiveness of single-scale feature extraction methods. To address this issue, we propose the Dual-Branch Blocked-Integration Self-Attention Network (DB-BISAN), a novel deep learning framework for EEG motor imagery classification. …”
Get full text

Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

“…Noisy data is a prevalent issue in data mining, significantly impacting the performance of classification algorithms. …”
Get full text

Enhancing Defect Classification in Solar Panels With Electroluminescence Imaging and Advanced Machine Learning Strategies by Fatih Demir

“…For the two-class classification problem, the classification performance is 98.17%, and for the four-class classification problem, it is 97.02%.…”
Get full text

Classification of commercial districts based on predicting the survival rate of food service market in Seoul. by DongHyeon Lee, Jaekyung Lee, ManSu Kang, SangHyun Cheon

Get full text

Profile of Animal Ecology Field trip: Description of Students’ Identification Skills and Classification Skills by Iwan Setia Kurniawan, Fransisca Sudargo Tapilouw, Topik Hidayat

“…The results showed that the CPL course and CPL subjects not relevant to the fact that in both CPL there are some points the use of science and technology, the reality in the learning process technology, it is also supported by student response on the issue. The identification and classification skills of students included in the category sufficient. …”
Get full text

Classification framework to identify similar visual scan paths using multiple similarity metrics by Ricardo Palma Fraga, Ziho Kang, Jerry Crutchfield

“…We applied our framework to the visual scan paths of nine tower controllers in a high-fidelity simulator when a “clear-to-take-off” clearance was issued. The classification framework was able to provide richer and more meaningful classifications of the visual scan paths compared to the results when using either the string edit algorithm or Jaccard coefficient similarity. …”
Get full text

L2R-MLP: a multilabel classification scheme for the detection of DNS tunneling by Emmanuel Oluwatobi Asani, Mojiire Oluwaseun Ayoola, Emmanuel Tunbosun Aderemi, Victoria Oluwaseyi Adedayo-Ajayi, Joyce A. Ayoola, Oluwatobi Noah Akande, Jide Kehinde Adeniyi, Oluwambo Tolulope Olowe

Get full text

Hierarchical Classification of Environmental Noise Sources Considering the Acoustic Signature of Vehicle Pass-Bys by Xavier VALERO, Francesc ALIAS

“…The proposed classification scheme yields an averaged classification accuracy of 92.5%, which is, in absolute terms, 3% higher than the baseline (a traditional flat classification scheme without hierarchical structure). …”
Get full text

Heart Sound Classification Based on Multi-Scale Feature Fusion and Channel Attention Module by Mingzhe Li, Zhaoming He, Hao Wang

“…In this paper, we propose a heart sound classification model named CAFusionNet, which fuses features from different layers with varying resolution ratios and receptive field sizes. …”
Get full text

Multiple Scaling Based EfficientNet Modelling for Liver Tumor Classification on CT Images by Bilga Jacob, R. S. Vinod Kumar, S. S. Kumar

“…Recent, deep Convolutional Neural Network (CNN) research has produced amazing improvements in image segmentation and classification. The same issue of diagnosing liver nodules in computed tomography (CT) scans is addressed in this research by introducing a novel Computer-Aided Detection (CAD) system that makes use of an Efficient Network (EfficientNet) image classification algorithm. …”
Get full text

Advanced heart disease classification based on multi-channel heart sound coupling features. by Yu Fang, Dongbo Liu, Zijian Guo, Hongxia Leng, Xing Liu, Xiaochen Wu

“…To address this issue, a novel classification framework based on multi-channel heart sound coupling feature extraction is proposed to enhance heart disease identification. …”
Get full text

A swin transformer and CNN fusion framework for accurate Parkinson disease classification in MRI by Sayyed Shahid Hussain, Pir Masoom Shah, Hussain Dawood, Xu Degang, Ahmad Alshamayleh, Muhammad Adnan Khan, Taher M. Ghazal

Get full text

Study of the Application of Text Augmentation with Paraphrasing to Overcome Imbalanced Data in Indonesian Text Classification by Mutiara Indryan Sari, Lya Hulliyyatus Suadaa

“…This study addresses the data imbalance issue in Indonesian text classification by proposing a novel text augmentation approach using fine-tuned pre-trained models: IndoGPT2, IndoBART-v2, and mBART50. …”
Get full text

Effective Land Use Classification Through Hybrid Transformer Using Remote Sensing Imagery by Muhammad Zia Ur Rehman, Syed Mohammed Shamsul Islam, Anwaar Ul-Haq, David Blake, Naeem Janjua

“…Recent advances in deep learning for hyperspectral image classification have shown exceptional performance in resource management and environmental planning through land use classification. …”
Get full text

Research on Fine-Grained Visual Classification Method Based on Dual-Attention Feature Complementation by Min Huang, Ke Li, Xiaoyan Yu, Chen Yang

“…An increasing number of fine-grained classification models utilize attention mechanisms to extract distinguishable regions to address this issue, yet they overlook other equally distinguishable but less obvious features. …”
Get full text

Dual-Domain Multi-Task Learning-Based Domain Adaptation for Hyperspectral Image Classification by Qiusheng Chen, Zhuoqun Fang, Shizhuo Deng, Tong Jia, Zhaokui Li, Dongyue Chen

“…Enhancing target domain discriminability is a key focus in Unsupervised Domain Adaptation (UDA) for HyperSpectral Image (HSI) classification. However, existing methods overlook bringing similar cross-domain samples closer together in the feature space to achieve the indirect transfer of source domain classification knowledge. …”
Get full text

Comparative Study on Different CNN Architectures Developed on Microstructural Classification in Al-Si Alloys by M.F. Kalkan, M. Aladag, K.J. Kurzydlowski, N.F. Yilmaz, A. Yavuz

“…This paper is an attempt to advance methods of microstructure recognition/classification/characterization by using Deep Learning approaches. …”
Get full text

CIL-LLM: Incremental Learning Framework Based on Large Language Models for Category Classification by WANG Xiaoyu, LI Xin, HU Mianning, XUE Di

“…To enhance classification accuracy in class-incremental learning (CIL) models for text classification and mitigate the issue of catastrophic forgetting, this paper introduces a CIL framework based on a large language model (CIL-LLM). …”
Get full text

Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. by Lingbo Li, Runpu Wang, Miaojie Zou, Fusen Guo, Yuheng Ren

“…However, existing deep learning-based garbage image classification models generally suffer from low classification accuracy, insufficient robustness, and slow detection speed due to the large number of model parameters. …”
Get full text

A Garbage Detection and Classification Method Based on Visual Scene Understanding in the Home Environment by Yuezhong Wu, Xuehao Shen, Qiang Liu, Falong Xiao, Changyun Li

“…Garbage classification is a social issue related to people’s livelihood and sustainable development, so letting service robots autonomously perform intelligent garbage classification has important research significance. …”
Get full text