This paper proposes an end-to-end deep hashing framework with category mask for fast video retrieval.
We present TRANX, a transition-based neural semantic parser that maps natural language (NL) utterances into formal meaning representations (MRs).
Semantic parsing is the task of transducing natural language (NL) utterances into formal meaning representations (MRs), commonly represented as tree structures.
Automated documentation of programming source code and automated code generation from natural language are challenging tasks of both practical and scientific interest.
Results are presented for a case study of targeting the Qualcomm Snapdragon 820 mobile computing platform for CNN deployment.