The original ImageNet dataset is a popular large-scale benchmark for training Deep Neural Networks.
We will present the design-techniques that became necessary in the development of the software that meets the above criteria, and demonstrate the power of our new design through experimental results and real world applications.
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese.
We present DiffTaichi, a new differentiable programming language tailored for building high-performance differentiable physical simulators.
In this paper, we present our on-going effort of constructing a large-scale benchmark, DeeperForensics-1. 0, for face forgery detection.
We detail a new framework for privacy preserving deep learning and discuss its assets.
This paper introduces wav2letter++, the fastest open-source deep learning speech recognition framework.