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MobDL: A framework for profiling deep learning models: A case study using mobile digital health applications
Version 2 2024-06-06, 10:59
Version 1 2021-11-17, 08:19
conference contribution
posted on 2024-06-06, 10:59 authored by ARM Forkan, PP Jayaraman, R Kaul, Yuxin ZhangYuxin Zhang, C Mccarthy, P Delir Haghighi, R RanjanMobDL: A framework for profiling deep learning models: A case study using mobile digital health applications
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Pagination
405-414Location
Darmstadt, GermanyPublisher DOI
Start date
2020-12-07End date
2020-12-09ISBN-13
9781450388405Language
engPublication classification
E1 Full written paper - refereedTitle of proceedings
MobiQuitous 2020 : Proceedings of the 17th EAI International Conference on Mobile and Ubiquitous Systems : Computing, Networking and ServicesEvent
EAI Mobile and Ubiquitous Systems : Computing, Networking and Services. Conference (17th : 2020 : Darmstadt, Germany)Publisher
Association for Computing MachineryPlace of publication
New York, N.Y.Usage metrics
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