Deep learning–based video analytics demands high network bandwidth to ferry the large
volume of data when deployed on the cloud. When incorporated at the edge side, only …

We propose the first mechanism to train object detection models from weak supervision in
the form of captions at the image level. Language-based supervision for detection is …

We introduce a novel training strategy for stereo matching and optical flow estimation that
utilizes image-to-image translation between synthetic and real image domains. Our …

Identification of the diffusion type of molecules in living cells is crucial to deduct their driving
forces and hence to get insight into the characteristics of the cells. In this paper, deep …

Current technological developments make human work increasingly automated. Computer
vision has widely used deep learning to help humans recognize objects. TensorFlow is a …

There has been active research focusing on lightweight approaches for on-device CNN
training. Convolutional neural network (CNN) training requires a substantial amount of …

More and more studies are looking at the use of dynamic off-chain transportation in IoT
systems that are based on payment channel networks (PCNs). Flexible routing in PCN …