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Rethinking Atrous Convolution for Semantic Image Segmentation

, , , and . (2017)cite arxiv:1706.05587Comment: Add more experimental results.

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Bayesian Inference on Multiscale Models for Poisson Intensity Estimation: Applications to Photon-Limited Image Denoising., , and . IEEE Trans. Image Processing, 18 (8): 1724-1741 (2009)Semantic Part Segmentation with Deep Learning., , , and . CoRR, (2015)Adaptive Multimodal Fusion by Uncertainty Compensation With Application to Audiovisual Speech Recognition., , , and . IEEE Trans. Speech Audio Process., 17 (3): 423-435 (2009)Poisson-Haar Transform: A nonlinear multiscale representation for photon-limited image denoising., , and . ICIP, page 3853-3856. IEEE, (2009)A Cross-Validatory Statistical Approach to Scale Selection for Image Denoising by Nonlinear Diffusion., and . CVPR (1), page 625-630. IEEE Computer Society, (2005)Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection., , and . CoRR, (2014)Image denoising in nonlinear scale-spaces: automatic scale selection via cross-validation., and . ICIP (1), page 481-484. IEEE, (2005)Adaptive Multimodal Fusion by Uncertainty Compensation with Application to Audio-Visual Speech Recognition., , , and . Multimodal Processing and Interaction, Springer, (2008)Adaptive multimodal fusion by uncertainty compensation., , , and . INTERSPEECH, ISCA, (2006)Perturb-and-MAP random fields: Using discrete optimization to learn and sample from energy models., and . ICCV, page 193-200. IEEE Computer Society, (2011)