Jeffrey Hightower
Electrical and Electronic Engineering · 2000–2008
A researcher in the Science corpus: 8 papers; trusts 12 researchers and is trusted by 61 researchers here, as inferred from the citation graph.
Subfields
- Electrical and Electronic Engineering — 20 citations into it; #389 of 16,539 by trust here, #2,036 by citations
- Computer Vision and Pattern Recognition — 17 citations into it; #3,914 of 21,575 by trust here, #3,732 by citations
- Artificial Intelligence — 11 citations into it; #23,835 of 35,345 by trust here, #17,776 by citations
- Computer Networks and Communications — 11 citations into it; #2,772 of 9,886 by trust here, #2,927 by citations
- Transportation — 7 citations into it; #1,986 of 2,062 by trust here, #177 by citations
Whom Jeffrey Hightower trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Paramvir Victor Bahl
- Dieter Fox
- Gaetano Borriello
- V. Padmanabhan
- Lance Doherty
- John Krumm
- Gregory D. Abowd
- Wolfram Burgard
- Kristofer S. J. Pister
- Sebastian Thrun
Who trusts Jeffrey Hightower overall
- Robert K. Harle
- Yi Shang
- Ivan Stojmenovic
- Kuo-Feng Ssu
- Kamol Kaemarungsi
- Oliver J. Woodman
- Dieter Fox
- Contributor Jennifer A. W. Wright
- G. Hoffmann
- Matt Duckham
Papers from Jeffrey Hightower's perspective
Ordered by how strongly the researchers Jeffrey Hightower trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- RADAR: an in-building RF-based user location and tracking system (Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064))
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Distinctive Image Features from Scale-Invariant Keypoints
- Going deeper with convolutions
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Location Systems for Ubiquitous Computing (2001) — 3,454 citations
- Bayesian Filtering for Location Estimation (2003) — 813 citations
- Place Lab: Device Positioning Using Radio Beacons in the Wild (2005) — 1,121 citations
- Mobility Detection Using Everyday GSM Traces (2006) — 334 citations
- Practical Metropolitan-Scale Positioning for GSM Phones (2006) — 315 citations
- The location stack: a layered model for location in ubiquitous computing (2002) — 297 citations
- The Mobile Sensing Platform: An Embedded Activity Recognition System (2008) — 649 citations
- SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength (2000) — 1,107 citations