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Dense Optical Flow for the Reconstruction of Weakly Textured and Structured Surfaces: Application to Endoscopy.

, , , , and . ICIP, page 310-314. IEEE, (2019)

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Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy., , , , , , , , , and 27 other author(s). Medical Image Anal., (2021)Mosaicing of Images with Few Textures and Strong Illumination Changes: Application to Gastroscopic Scenes., , , and . ICIP, page 1263-1267. IEEE, (2018)PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment., , , , , , , , , and 4 other author(s). CoRR, (2021)Multi-Scale Structural-aware Exposure Correction for Endoscopic Imaging., , , , , , , and . ISBI, page 1-5. IEEE, (2023)Multispectral Endoscopy to Identify Precancerous Lesions in Gastric Mucosa., , , , , , and . ICISP, volume 8509 of Lecture Notes in Computer Science, page 43-51. Springer, (2014)Evaluating object detector ensembles for improving the robustness of artifact detection in endoscopic video streams., , , , , , and . CoRR, (2022)Deep learning-based image exposure enhancement as a pre-processing for an accurate 3D colon surface reconstruction., , , , and . CoRR, (2023)Analysis of Multispectral Images of Excised Colon Tissue Samples Based on Genetic Algorithms., , , , , and . SITIS, page 833-838. IEEE Computer Society, (2012)Dense Optical Flow for the Reconstruction of Weakly Textured and Structured Surfaces: Application to Endoscopy., , , , and . ICIP, page 310-314. IEEE, (2019)Endoscopy disease detection challenge 2020., , , , , , , , , and . CoRR, (2020)