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Author

T. Le

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Sep 2026

SOTS: Leveraging Self-supervised Pretraining for Label-Efficient Ovarian Tumor Segmentation in Ultrasound Images.

A Self-supervised Ovarian Tumor Segmentation (SOTS) framework that leverages unlabeled ultrasound images to learn robust feature representations and achieves segmentation accuracy comparable to fully supervised U-Net variants while requiring substantially fewer annotations is proposed.

Hoang-Son Bui, T. Dao, T. Le · 0 citations
Conference Jul 2026

A Novel Dataset and Practical Deployment for Gesture-Based Human-Collaborative Robot Interaction

Collaborative robot or COBOT has emerged as a key advancement in robotics, significantly transforming industrial automation. Consequently, real-time gesture recognition for human-COBOT interaction has recently garnered significant attention. However, both datasets designed for practical robot control scenarios and end-...

Ha-Anh Nguyen, A. Nguyen, Duy-Anh Doan et al. · 0 citations
Jul 2026

CSA-SegNet: enhancing ovarian tumor segmentation from ultrasound images with spatial pooling and contour-based loss functions

A new loss function is proposed that enhances conventional loss functions such as IoU loss, SSIM Loss, and Focal loss function with Active Contour Euler Elastical loss with effectiveness in enhancing segmentation accuracy and boundary delineation of ovarian ultrasound images.

Thi-Loan Pham, Hoang-Son Bui, Van-Hung Le et al. · 0 citations

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