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Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.

, , , , , and . IEEE Trans. Med. Imaging, 39 (2): 514-525 (2020)

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Detecting object boundaries using low-, mid-, and high-level information., , and . Computer Vision and Image Understanding, 114 (10): 1055-1067 (2010)Spatiotemporal information storage in a content addressable memory using realistic neurons., and . Neural Networks, 7 (3): 419-439 (1994)Dimension reduction, generalized deformable models and the development of ocularity and orientation., , and . Neural Networks, 9 (2): 309-319 (1996)Temporally consistent region-based video exposure correction., , , and . ICME, page 1-6. IEEE Computer Society, (2015)Learning Like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images., , , , , and . ICCV, page 2533-2541. IEEE Computer Society, (2015)Image Parsing: Unifying Segmentation, Detection, and Recognition., , , and . ICCV, page 18-25. IEEE Computer Society, (2003)Bottom-Up Segmentation for Top-Down Detection., , , and . CVPR, page 3294-3301. IEEE Computer Society, (2013)PASCAL Boundaries: A Semantic Boundary Dataset with a Deep Semantic Boundary Detector., , , and . WACV, page 73-81. IEEE Computer Society, (2017)Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion., , , , and . ECCV (2), volume 5303 of Lecture Notes in Computer Science, page 759-773. Springer, (2008)Deep Co-Training for Semi-Supervised Image Recognition., , , , and . ECCV (15), volume 11219 of Lecture Notes in Computer Science, page 142-159. Springer, (2018)