all AI news
ExpansionNet v2: Block Static Expansion in fast end to end training for Image Captioning. (arXiv:2208.06551v2 [cs.CV] UPDATED)
Aug. 17, 2022, 1:12 a.m. | Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi
cs.CV updates on arXiv.org arxiv.org
Expansion methods explore the possibility of performance bottlenecks in the
input length in Deep Learning methods. In this work, we introduce the Block
Static Expansion which distributes and processes the input over a heterogeneous
and arbitrarily big collection of sequences characterized by a different length
compared to the input one. Adopting this method we introduce a model called
ExpansionNet v2, which is trained using our novel training strategy, designed
to be not only effective but also 6 times faster compared …
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Business Intelligence Analyst
@ Rappi | COL-Bogotá
Applied Scientist II
@ Microsoft | Redmond, Washington, United States