… 3 platform to 1) facilitate efficient deep learning research in … The NiftyNet platform comprises
an implementation of the … deep learning research to new clinical applications with a shallow …

… In Section IV, we outline various common platforms for implementing deep learning architec…
cations of deep learning. In Section VI, we highlight areas of future deep learning application …

… This paper introduces Mariana, the Tencent deep learning platform to accelerate training,
support large model, and simplify experiments for various of applications in Tencent. Mariana …

… deep learning platform in China, is introduced comprehensively. [Methods] In this paper, a
brief history of the deep learning … core framework, toolkits and service platforms. After that, we …

… learning models. In this paper, we present SINGA1, a general distributed deep learning
platform… model that supports a variety of popular deep learning models, namely feed-forward …

… In this paper, we present our design of a scalable seismic analytics platform built upon Apache
… the deep learning technology we employed in our experiments using the platform and the …

… , we herein introduce Deep Docking (DD), a novel deep learning platform that is suitable for
… The DD approach utilizes quantitative structure–activity relationship (QSAR) deep models …

… In this work, we introduced a deep learning platform for image-based plant phenotyping
called Deep Plant Phenomics. We demonstrated its effectiveness by performing three image-…

… To address this problem, we developed a deep learning approach to discriminate … Deep
learning is a type of artificial intelligence (AI) that uses multiple computational layers in a deep …

Deep learning (DL) models are inherently vulnerable to adversarial examples – maliciously
crafted inputs to trigger target DL models to misbehave – which significantly hinders the …