Daniel Roggen

Biomedical Engineering · IEEE Transactions on Information Technology in Biomedicine · 2008–2019

A researcher in the Science corpus: 8 papers; trusts 54 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Biomedical Engineering — 99 citations into it; #1,334 of 10,734 by trust here, #2,835 by citations
• Computer Vision and Pattern Recognition — 34 citations into it; #5,775 of 21,575 by trust here, #4,887 by citations
• Cognitive Neuroscience — 28 citations into it; #10,373 of 10,852 by trust here, #9,453 by citations
• Artificial Intelligence — 21 citations into it
• Human-Computer Interaction — 15 citations into it; #2,138 of 2,253 by trust here, #1,907 by citations
• Computer Networks and Communications — 12 citations into it
• Signal Processing — 10 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Daniel Roggen trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Honglak Lee
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Yann LeCun
6. Attila Reiss
7. Alex Graves
8. Yann Dauphin
9. Andreas Bulling
10. Diederik P. Kingma

Who trusts Daniel Roggen overall

1. Sreenivasan Ramasamy Ramamurthy
2. Dhanesh Ramachandram
3. Dana Hughes
4. Andreas Bulling
5. Ziqi Zhang
6. Yu Guan
7. Florenc Demrozi
8. Mikel Canizo
9. Jindong Wang
10. Satya Prakash Singh

Papers from Daniel Roggen's perspective

Ordered by how strongly the researchers Daniel Roggen trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Going deeper with convolutions
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition (2016) — 2,615 citations
• Recognition of visual memory recall processes using eye movement analysis (2011) — 129 citations
• Potentials of Enhanced Context Awareness in Wearable Assistants for Parkinson's Disease Patients with the Freezing of Gait Syndrome (2009) — 80 citations
• Wearable Assistant for Parkinson’s Disease Patients With the Freezing of Gait Symptom (2010) — 675 citations
• Flexible Sensors—From Materials to Applications (2019) — 201 citations
• The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition (2013) — 761 citations
• Wearable Activity Tracking in Car Manufacturing (2008) — 381 citations
• Activity Recognition from On-Body Sensors: Accuracy-Power Trade-Off by Dynamic Sensor Selection (2008) — 364 citations