3 accepted papers
Traditional magnetic tactile sensors are highly susceptible to external magnetic field interference, limiting their reliability in practical applications. To address this challenge, we propose a dual-modal soft magnetic skin capable of simultaneously acquiring magnetic and force tactile information
Binary neural networks (BNNs) contribute a lot to the efficiency of image classification models. However, in dense predication tasks such as human pose estimation, predictions in different locations are coupled and rely on the extraction of features across entire images. As a result, more robust and…
Training accurate deep neural networks in the presence of noisy labels is an important task. Though a number of approaches have been proposed for learning with noisy labels, many open issues remain. In this paper, we show that DNN learning with Cross Entropy is not robust to label noise and exhibits…