Matthai Philipose
Computer Vision and Pattern Recognition · 2004–2019
A researcher in the Science corpus: 19 papers; trusts 604 researchers and is trusted by 86 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 165 citations into it; #3,410 of 21,575 by trust here, #3,345 by citations
- Artificial Intelligence — 114 citations into it; #15,820 of 35,345 by trust here, #8,810 by citations
- Efficiency & Compression — 45 citations into it
- Model Architectures — 44 citations into it
- Signal Processing — 40 citations into it
- Optimization & Training — 18 citations into it
- Natural Language Processing — 14 citations into it
- Media Technology — 10 citations into it
Whom Matthai Philipose trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Karen Simonyan
- Yann LeCun
- Andrew Zisserman
- Ilya Sutskever
- Diederik P. Kingma
Who trusts Matthai Philipose overall
- Diane Joyce Cook
- Xiaofeng Ren
- Vincent Wenchen Zheng
- Parisa Rashidi
- Du Tran
- Liming Luke Chen
- Narayanan Chatapuram Krishnan
- Michael Buettner
- Giovanni Acampora
- Bin Guo
Papers from Matthai Philipose's perspective
Ordered by how strongly the researchers Matthai Philipose 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)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- A Scalable Approach to Activity Recognition based on Object Use (2007) — 399 citations
- Egocentric recognition of handled objects: Benchmark and analysis (2009) — 121 citations
- Inferring activities from interactions with objects (2004) — 823 citations
- Fine-grained activity recognition by aggregating abstract object usage (2005) — 527 citations
- Courteous glass (2014) — 33 citations
- Blending LSTMs into CNNs (2015) — 61 citations
- Battery-free wireless identification and sensing (2005) — 294 citations
- Recognizing daily activities with RFID-based sensors (2009) — 323 citations
- Mapping and localization with RFID technology (2004) — 830 citations
- Nexus: a GPU cluster engine for accelerating DNN-based video analysis (2019) — 335 citations
- Focus: Querying Large Video Datasets with Low Latency and Low Cost (2018) — 304 citations
- Heterogeneous Bitwidth Binarization in Convolutional Neural Networks (2018) — 29 citations
- Real-Time Video Analytics: The Killer App for Edge Computing (2017) — 492 citations
- Live Video Analytics at Scale with Approximation and Delay-Tolerance (2017) — 485 citations
- Analysis of Deep Neural Networks with Extended Data Jacobian Matrix (2016) — 38 citations
- MCDNN: An Approximation-Based Execution Framework for Deep Stream Processing Under Resource Constraints (2016) — 413 citations
- Do Deep Convolutional Nets Really Need to be Deep and Convolutional? (2016) — 259 citations
- A Long-Term Evaluation of Sensing Modalities for Activity Recognition (2007) — 441 citations
- Unsupervised Activity Recognition Using Automatically Mined Common Sense (2005) — 316 citations