Bodhi Priyantha
Computer Vision and Pattern Recognition · 2001–2019
A researcher in the Science corpus: 9 papers; trusts 160 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 68 citations into it; #10,578 of 21,575 by trust here, #6,737 by citations
- Electrical and Electronic Engineering — 63 citations into it; #3,219 of 16,539 by trust here, #4,925 by citations
- Artificial Intelligence — 59 citations into it
- Computer Networks and Communications — 56 citations into it; #3,860 of 9,886 by trust here, #2,044 by citations
- Ocean Engineering — 21 citations into it; #1,729 of 3,193 by trust here, #1,086 by citations
- Neural Architecture Search & AutoML — 19 citations into it
- Model Architectures — 16 citations into it
- Optimization & Training — 9 citations into it
Whom Bodhi Priyantha trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Paramvir Victor Bahl
- Dragos Stefan Niculescu
- Chris Savarese
- Simon Josefsson
- Hari Balakrishnan
- N. Priyantha
- Ananth Rao
- Lewis Girod
- Moustafa Youssef
- Radhika Nagpal
Who trusts Bodhi Priyantha overall
- Souvik Sen
- Dominique Guinard
- Guoqiang Mao
- Sylvia Ratnasamy
- Dragos Stefan Niculescu
- Mike Hazas
- Vlad M. Trifa
- Baris Fidan
- Bozidar Radunovic
- Deze Zeng
Papers from Bodhi Priyantha's perspective
Ordered by how strongly the researchers Bodhi Priyantha trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
Their papers
- Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours (2019) — 291 citations
- The cricket compass for context-aware mobile applications (2001) — 686 citations
- FM-based indoor localization (2012) — 332 citations
- Tracking moving devices with the cricket location system (2004) — 488 citations
- Tiny web services: design and implementation of interoperable and evolvable sensor networks (2008) — 336 citations
- Mobile-assisted localization in wireless sensor networks (2005) — 317 citations
- Surviving wi-fi interference in low power ZigBee networks (2010) — 416 citations
- Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization (2019) — 37 citations
- The Cricket indoor location system (2005) — 551 citations