Institute of Neuroinformatics
University of Zürich and ETH Zürich, Switzerland
For more information, please click here for my current CV.
2.1 Research Interests
- Deep Neural Networks
- Event-based Learning and Processing
- Feature Learning
- Computer Vision
- Robotic Vision
- Image Processing
- Artificial General Intelligence
- Theory of Everything
2.2 Active Projects
- Learning Deep Learning: A Deep Learning reading list.
- macman: Handy tools for Mac OS X terminal.
- en2pinyin: Character-level Chinese text generation and translation.
- PySealer: Yet another standalone Python application creator.
- DDD17+: 53-Hour End-To-End DAVIS Driving Dataset.
2.3 Completed Projects
- DVS Benchmark Datasets for Object Tracking, Action Recognition, and Object Recognition
- Max-Pooling Operations in Deep Spiking Neural Networks
- Learning to Navigate without a Map
- Understanding Iterative Estimation in Gated Neural Networks
Mac OS X
Smart Girl Engineer
Cats and Dogs pics
Kid that isn't mine
Accidentally find a nice song
Tom Hanks in girl's voice
New Emacs Tricks
Reading Endless Article
Machine Learning in Browser
Write in Emacs
Recurrent Neural Networks
Low Network Speed
Cannot Explain Myself Precisely
Another Meeting Delay
Fake Social Manners
Around with People who I don't like
All kinds of reunion
Ambush my back
Things out of control
Have no idea about what's next
Coders who don't follow standards
Person who refuses to learn useful things
B. Rueckauer, I-A. Lungu, Y. Hu, M. Pfeiffer, S-C. Liu, “Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification”, Frontiers in Neuroscience, 11:682, 2017.
B. Reckauer, I-A. Lungu, Y. Hu, M. Pfeiffer, “Theory and Conversion of Analog to Spiking Convolutional Neural Netowrks” in Computing with Spikes NIPS 2016 Workshop, Barcelona, Spain, 2016.
Y. Hu, H. Liu, M. Pfeiffer, T. Delbruck, “DVS Benchmark Datasets for Object Tracking, Action Recognition and Object Recognition”, Frontiers in Neuroscience, 10:405, 2016.
DNT. How, Y. Hu, KSM. Sahari, CK. Loo, “ Multiple Sequence Behavior Recognition on Humanoid Robot using Long Short-term Memory (LSTM)” in 2014 IEEE International Symposium on Robotics and Manufacturing Automation (ROMA 2014), Kuala Lumpur, Malaysia, 2014.
Y. Hu, DNT. How, KSM. Sahari, CK. Loo, “Learning Sufficient Representation for Spatio-temporal Deep Network Using Information Filter” in 2014 IEEE/SICE International Symposium on System Integration, Korakuen Campus, Chuo University, Tokyo, Japan, 2014.
Y. Hu, CK. Loo, “A Generalized Quantum-Inspired Decision Making Model for Intelligent Robot”, The Scientific World Journal, vol. 2014, Article ID 240983, 8 pages, 2014.
Y. Hu, WL. Hoo, CS. Chan, “Clustering Algorithms for Scene Classification — A Performance Comparison between K-means; Fuzzy c-means and GMM” in IIEEJ 3rd Image Electronics and Visual Computing Workshop, Kuching, Malaysia, 2012, IIEEJ.