Accurate localization of the upper end vertebra (UEV), lower end vertebra (LEV), and apex vertebra (AV) is essential for automated scoliosis assessment and Cobb angle measurement. This study proposes a geometry-aware, multi-task sequence learning framework for vertebral landmark localization and scoliosis type classifi...
Pei-Cheng Kuo, Yen-Ching Chang· Machine Learning and Knowled...· 0 citations
Tomato leaf diseases can significantly reduce crop yield and quality, creating a need for accurate and efficient automated diagnostic systems. This paper presents LiteAttNet, a lightweight attention-enhanced framework for tomato leaf disease classification. The proposed architecture integrates a MobileNetV3Large backbo...
Alok Kumar Sharma, Yung-Fa Huang, Tan-Hsu Tan et al.· International Conference on...· 0 citations
This work proposes a novel, highly efficient Triple-Path Kolmogorov–Arnold Network (KAN) optimized via Deep Mutual Learning (DML), which establishes a robust, accurate, and clinically viable solution for automated point-of-care retinal diagnostics.
This research evaluates the performance of SegNet, U-Net, and DeepLab across in-domain, cross-domain, and mixed-domain scenarios, demonstrating that lightweight models often offer the optimal balance between performance and operational efficiency.
