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Learning deep structured network for weakly supervised change detection.

, , , , , and . IJCAI, page 2008-2015. ijcai.org, (2017)

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Review of 3D object representation techniques for automatic object recognition., and . VCIP, volume 4067 of Proceedings of SPIE, page 1185-1197. SPIE, (2000)Learning Distributions of Meant Color., , , and . CoRR, (2017)On Decomposing an Unseen 3D Face into Neutral Face and Expression Deformations., , and . ICB, volume 5558 of Lecture Notes in Computer Science, page 22-31. Springer, (2009)Faster R-CNN Based Deep Learning for Seagrass Detection from Underwater Digital Images., , , and . DICTA, page 1-7. IEEE, (2019)Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes., , and . IEEE Trans. Pattern Anal. Mach. Intell., 28 (10): 1584-1601 (2006)Deep Learning for Scene Understanding., , , , and . Handbook of Deep Learning Applications, Springer, (2019)SC-CAN: Spectral Convolution and Channel Attention Network for Wheat Stress Classification., , , , , , and . Remote. Sens., 14 (17): 4288 (2022)SkeletonNet: Mining Deep Part Features for 3-D Action Recognition., , , , and . IEEE Signal Process. Lett., 24 (6): 731-735 (2017)A comparative study on optical flow for facial expression analysis., , , , and . Neurocomputing, (2022)Untrained Neural Network Priors for Inverse Imaging Problems: A Survey., , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (5): 6511-6536 (May 2023)