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ai:0-contents [2007/05/18 21:21]
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-====== Catalog of methods in AI/vision/robotics ====== 
- 
-This is a classification of techniques and algorithms, giving only keywords ... 
- 
-===== Learning ===== 
-==== Supervised learning ==== 
-=== Classification === 
- 
-  * **MLP (Multi Layers Perceptron)** - //PMC (Perceptron multicouches)// 
-    * __gradient backpropagation__ - //rétropropagation du gradient// 
-      * __stochastic__ 
-      * __with inertia__ 
-      * __simulated annealing__ - //recuit simulé// 
-    * __newton__ (second order) 
-  * **RBFNN (Radial Basis Functions Neural Networks)** 
-    * __k-means then gradient descent__ 
-    * __incremental addition of neurons then exact method__ 
-  * **SVM (Support Vectors Machine)** 
-  * **Decision tree** - //arbre de décision// 
-    * __ID3__ (based on entropy) 
-  * __**k-nearest neighbors**__ - //k plus proches voisins// 
-  * **Boosting** 
-    * __AdaBoost__ (ADAptive BOOSTing) 
-      * __Discrete AdaBoost__ 
-      * __Real AdaBoost__ 
-      * __Gentle AdaBoost__ 
-      * __LogitBoost__ 
-      * __FloatBoost__ 
-      * __AdaBoost.Reg__ 
-      * __Multiclass AdaBoost.M1__ 
-      * __Multiclass AdaBoost.M2__ 
-      * __Multilabel AdaBoost.MR__ 
-      * __Multilabel AdaBoost.MH__ 
-      * __SAMME__ (Stagewise Additive Modeling using a Multi-class Exponential loss function) 
-      * __GAMBLE__ (Gentle Adaptive Multiclass Boosting Learning) 
-    * __LPBoost__ (Linear Programming BOOSTing) 
-    * __TotalBoost__ 
-    * RotBoost 
-    * alphaBoost 
-    * CGBoost (Conjugate Gradient BOOSTing) 
-    * __Bootstrap Aggregating__ 
-  * **Cascades of detectors** [[classification#cascades_of_detectors|[+] ]] 
-  * **Trees of detectors** 
- 
-=== Regression === 
- 
-  * **MLP (Multi Layers Perceptron)** 
-  * **RBFNN (Radial Basis Functions Neural Network)** 
-  * **SVR (Support Vectors Regressor)** 
- 
-=== Pattern recognition === 
- 
-  * __**Viola-Jones Detector**__ 
-    * with extended set of haar features 
-    * Rotation Invariant 
- 
-==== Unsupervised learning ==== 
-=== Vector quantization / Clustering === 
- 
-  * __**Sequential leader**__ 
-  * __**k-means**__ - //k-moyennes// 
-  * __**GNG (Growing Neural Gas)**__ 
-  * __**Auto-organizing maps (Kohonen)**__ - //cartes auto-organisatrices de Kohonen// 
- 
- 
-==== Reinforcement learning ==== 
- 
-  * **MDP (Markov Decision Processes)** 
-    * __Q-learning__ 
-    * __Value iteration__ 
-    * __Policy iteration__ 
- 
-===== Planification ===== 
- 
-==== Symbolic ==== 
-=== State space search === 
- 
-  * __A*__ 
-    * __WA*__ 
-    * __IDA*__ 
-  * __Dijkstra__ 
- 
-=== Logics === 
- 
-  * __**GraphPlan**__ 
-    * __Stan__ 
-    * __IPP__ 
-    * __SGP__ 
-  * __**SATplan (SATisfiability PLANning)**__ 
- 
-==== Others ==== 
- 
-  * **Genetic algorithms** - //algorithmes génétiques// 
-  * **Ant colonies** - //colonies de fourmis// 
- 
-==== Specific ==== 
-=== Path planning === 
- 
-  * **Configurations space** 
-  * **Potential fields** 
- 
-===== Perception ===== 
-==== Vision ==== 
- 
-=== Color Quantization === 
- 
-  * **RGB cone** 
-  * **YUV polygon** 
-  * **HSV rectangle** 
-  * **Lab** 
- 
-=== Image segmentation === 
- 
-  * **Floodfill** - //inondation// 
-  * **Watershed** - //lignes de partage des eaux// 
- 
-=== Filters === 
- 
-  * Anti-noise (smoothing) 
-    * __Median Filter__ - //filtre médian// 
-    * __Vector Median Filter__ 
-    * __Kuwahara filter__ 
-    * __Peer Group Filtering__ 
-    * __Anisotropic Filtering__ 
-  * Gradient 
-    * __Prewitt__ [[vision#prewitt|[+] ]] 
-    * __Roberts__ 
-    * __Sobel__ 
-    * __Laplace__ 
-    * __Scharr__ 
-  * Morphological 
-    * __dilation__ - //dilatation// 
-    * __erosion__ - //érosion// 
-    * __opening__ - //ouverture// 
-    * __closing__ - //fermeture// 
- 
-=== Edge detection === 
- 
-  * __**Canny detector**__ 
-    * __Canny-Deriche__ 
-  
-=== Pattern recognition === 
- 
-  * __**Mean-Square Regression**__ - //Régression aux moindres carrés// 
-  * **Hough Transforms** 
-    * __Standard Hough Transform__ 
-    * __Randomized Hough Transform__ 
-    * __Connective Randomized Hough Transform__ 
-    * __Combinatorial Hough Transform__ 
-    * __Adaptive Hough Transform__ 
-    * __Probabilistic Hough Transform__ 
-    * __Adaptive Probabilistic Hough Transform__ 
-    * __Progressive Probabilistic Hough Transform__ 
-    * __Hierarchical Hough Transform__ 
-    * __Sampling Hough Transform__ 
-    * **Generalized Hough Transform** 
-  * **UpWrite method** 
-  * **Curvogram** 
- 
-=== Tracking === 
- 
-  * __**Kalman Filter**__ 
-    * Generalized Kalman Filter 
-  * **Correlation Tracking** 
-    * __ACA__ (Area Correlation Algorithm) 
-  * __KLT Tracker__ (Kanade-Lucas-Tomasi) 
-  * __IPAN Tracker__ 
-  * __MeanShift__ 
-  * Features detection 
-    * __Harris detector__ 
-    * __Susan detector__ 
-    * __Multiresolution Contrast detector__ 
- 
-==== Sensors fusion ==== 
- 
-  * __**Kalman filter**__ 
-  * **Particles filter** (bayesian network) - //filtrage particulaire// 
  
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