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Swarnendu Ghosh, Teresa Gonçalves and Nibaran Das
Conceptual representations of images involving descriptions of entities and their relations are often represented using scene graphs. Such scene graphs can express relational concepts by using sets of triplets ⟨subject—predicate&...
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Dongwei Qiu, Haorong Liang, Zhilin Wang, Yuci Tong and Shanshan Wan
Quickly and accurately identifying water leakage is one of the important components of the health monitoring of subway tunnels. A mobile vision measurement system consisting of several high-resolution, industrial, charge-coupled device (CCD) cameras is p...
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Yaojie Zhang, Huahu Xu, Junsheng Xiao and Minjie Bian
The real world is full of noisy labels that lead neural networks to perform poorly because deep neural networks (DNNs) are prone to overfitting label noise. Noise label training is a challenging problem relating to weakly supervised learning. The most ad...
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David Kartchner, Davi Nakajima An, Wendi Ren, Chao Zhang and Cassie S. Mitchell
A major bottleneck preventing the extension of deep learning systems to new domains is the prohibitive cost of acquiring sufficient training labels. Alternatives such as weak supervision, active learning, and fine-tuning of pretrained models reduce this ...
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Shikha Dubey, Abhijeet Boragule, Jeonghwan Gwak and Moongu Jeon
Given the scarcity of annotated datasets, learning the context-dependency of anomalous events as well as mitigating false alarms represent challenges in the task of anomalous activity detection. We propose a framework, Deep-network with Multiple Ranking ...
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