When physics based vision meets deep learning, there will be mutual benefits. On one hand, classic physics based vision tasks can be implemented in a data-fashion way to handle complex scenes. This is because, a physically more accurate optical model can be too complex as an inverse problem ...
Join us at the 4th International Workshop where Physics Based Vision converges with Deep Learning, held in conjunction with CVPR2024. This workshop explores the synergy between physics-based vision and deep learning, fostering mutual benefits and advancements in various vision tasks. [Topics of Inter...
Vision meets robotics: The kitti dataset. The Inter- national Journal of Robotics Research, 32(11):1231–1237, 2013. 8 [27] Markus Giftthaler, Michael Neunert, Markus Stäuble, and Jonas Buchli. The control toolbox—an open-source c++ li- brary for robotics...
In Proc. 36th International Conference on Machine Learning (eds Chaudhuri, K. & Salakhutdinov, R.) 5301–5310 (PMLR, 2019). Chattopadhyay, A. & Hassanzadeh, P. Long-term instabilities of deep learning-based digital twins of the climate system: the cause and a solution. Preprint at https:...
Similar to many fields of sciences, recent deep learning advances have been applied extensively in geosciences for both small- and large-scale problems. However, the necessity of using large training data and the ‘black box’ nature of learning have limited them in practice and difficult to inte...
Anatomy-based PVE correction allows for accurate SPECT quantification of the 177Lu activity concentration with realistic kidney geometries. Combined with recent progress in deep-learning algorithms for automatic anatomic segmentation of whole-body CT, these methods could be of particular interest for a fu...
With MW, simulated random rates agreed well with singles-based randoms, and NECR obtained with MW exceeded that from SW at all activity levels, increasing as expected with axial length of the scanner. fMC studies indicate a ULD of 585 keV is optimal for 89Zr imaging. Conclusions fMC ...
Energy and policy considerations for modern deep learning research. AAAI 34, 13693–13696 (2019). Article Google Scholar Nvidia AI. BERT meets GPUs. Medium https://medium.com/future-vision/bert-meets-gpus-403d3fbed848 (2020). Schneidman, E., Freedman, B. & Segev, I. Ion channel ...
18601200232@163.com, wangxt@126.com, figoleilei@163.com, wmzuo@hit.edu.cn Abstract Although deep neural networks have achieved astonish- ing performance in many vision tasks, existing learning- based methods are far inferior to the physical model-based sol...
Proceedings of the IEEE conference on computer vision and pattern recognition. 2017. ^Lee, Juho, et al. "Set transformer: A framework for attention-based permutation-invariant neural networks." International conference on machine learning. PMLR, 2019. ^Worrall, Daniel, and Max Welling. "Deep ...