On-device neural network training has emerged as a key enabler for privacy-preserving and personalized data processing at the edge. However, the deployment of Few-Shot Learning …
Sensors capture large volumes of data containing both critical and redundant information for neural network (NN) inference. However, limited bandwidth and energy efficiency at the …
In this letter, we predict the locations as probability distributions for the tasks of image object detection. We adopt the Kullback-Leibler divergences as the regression losses to …
Convolutional neural network (CNN), one of the branches of deep neural networks, has been widely used in image recognition, natural language processing, and other related fields …
Recently, studies on single image super-resolution using Deep Convolutional Neural Networks (DCNN) have been demonstrated to have made outstanding progress over conventional …