Possible working groups : list of key-words
Français / English
Not sorted
Ariana (global list)
- Optimization
- convex
- non convex
- combinatorial (on graphs)
- simulated annealing and others...
- Shape analysis
- differential geometry (manifolds, etc)
- geodesics...
- Invariance theory
- geometric invariants
- radiometric...
- Stochastic geometry
- Fast programming
- with GPU
- with CPU
- parallel computing
Thierry (Cortex)
- Learning
- learning methods that work in practice and which are applied to many domains (how does it work, why ?, etc)
- For example : SVM, Vapnik theory, etc
François (Pulsar)
- Learning
- learning methods that work in practice and which are applied to many domains (how does it work, why ?, etc)
- Graph based learning : HMM, DBN, etc
- kernel based learning : SVM, Vapnik theory, etc
- On-line and incremental learning - Long term and continuous learning
- Optimization
- parameter tuning: simplex, ransac, graph cuts
- convex
- non convex
- combinatorial (on graphs)
- simulated annealing and others...
- Image features: HOG, SIFT, MSER, KLT,...
Annie (Pulsar)
- Stochastic grammars
- and their analysis tools
Bernard (Pulsar)
- GPU
- GPGPU : General Purpose Computation Using Graphics Hardware
(http://www.gpgpu.org/)
- Tools (openVidia : a GPU accelerated Computer Vision
Library, etc...)
- Implementation of algorithms ....
- etc...
- Interesting libraries (Numerical recipes (http://www.nr.com/),
openCV, LTI-Lib, QT, wxWidget, etc....)
- Shape representations (splines, statistiques, etc...) and
comparison ...
- People modelling (silhouettes, etc)
- Learning
Keywords by people who left
Lan (Pulsar)
- Video indexing
- Video retrieval
- Object matching
- Similarity measures
- Relevance feedback or User interaction
Pierre (Ariana)
- Optimization methods
- convex problems
- non convex problems
Suresh (Pulsar)
I prefer concepts in machine learning and optimization. In specific,
- Machine learning
- On-line and incremental learning - Long term and continuous learning
- Self-supervised learning
- Learning with loss - active and passive forgetting
- Optimization
- Particle swarm optimization for nonlinear search
- Active classifier and Search