Keywords:
- (adaptive) learning rate
- activation function
- active shape model
- adaptive steepness
- appearance
- backpropagation
- backpropagation neural networks
- bias
- Boolean logic
- comparison of weight initialization methods
- complexity
- connectionism
- construction of networks
- contour tracking
- edge template
- Eigenface model
- gain
- generalization
- generalization performance
- graph theory
- high order neural network
- high order perceptron
- high order perceptrons
- high(er) order neural network
- high(er) order perceptron
- histogram
- illumination variation
- initial weight
- initial weight distribution
- initial weights
- interconnection strength
- joined forward-backward tracking
- learing rate
- learning rate
- model error
- multilayer neural network
- multilayer perceptron
- nets
- network size
- network topology
- neural computation
- neural computing
- neural network
- neural network connectivity
- neural network initialization
- neural network optimization
- neural network simulator
- neural network topology
- neurocomputing
- object-oriented
- ontogenic neural network
- OpenSimulator
- optical implementation
- optimal model
- optimal network size
- optimality criteria
- optimization
- parameters
- pattern matching
- point distribution model
- pruning
- random weight initialization
- real-world benchmark
- Sesame
- shape models
- shape parameters
- sigma-pi connection
- Sigma-Pi neural network
- sigmoid steepness
- slope
- topology
- training time
- weight initialization
Publications of Georg Thimm sorted by title
A
| A Boolean Approach to Construct Neural Networks for Non-Boolean Problems, and , in: Proceedings of the 8th IEEE International Conference on Tools with Artificial Intelligence, IEEE, 1996 |
B
| Boolean Logic Inspired High Order Perceptron Construction, , and , in: SIPAR Workshop'95 Parallel and Distributed Systems, SIPAR SI Group for Parallel Systems, Biel School of Engineering, Computer Science Department, 1995 |
|
C
| Calendar of meetings (several issues), , in: Neurocomputing, 1997 |
E
| Evaluating pruning methods, and , in: 1995 International Symposium on Artificial Neural Networks (ISANN'95), 1995 |
|
| Evaluating the Complexity of Databases for Person Identification and Verification, , and , in: 8th Int. Conf. Computer Analysis of Images and Patterns, Springer Verlag, 1999 |
|
| Evaluating the Complexity of Databases for Person Identification and Verification, , and , Idiap-RR-10-1998 |
|
| Extraction of Articulators in X-Ray Image Sequences, and , in: Proceedings of the European Conference on Speech Communication and Technology, 1999 |
|
G
| Gain Elimination form Backpropagation Neural Networks, , and , in: Proceedings of the International Conference on Neural Networks, IEEE, Perth, IEEE, 1995 |
H
| High Order and Multilayer Perceptron Initialization, and , Idiap-RR-07-1994 |
|
| High Order and Multilayer Perceptron Initialization, and , in: IEEE Transactions on Neural Networks, 8(02), 1997 |
I
| Illumination-robust Pattern Matching Using Distorted Color Histograms, and , in: Pattern Recognition and Image Understanding, Infix, 1999 |
| Illumination-robust Pattern Matching Using Distorted Color Histograms, and , Idiap-RR-09-1998 |
|
M
| Modular Object-Oriented Neural Network Simulators and Topology Generalizations, , and , in: Proceedings of the International Conference on Artificial Neural Networks (ICANN 94), Sorrento, Italy, Springer-Verlag, 1994 |
|
N
| Neural Network Initialization, and , in: From Natural to Artificial Neural Computation, Springer Verlag, 1995 |
| Neural Network Pruning and Pruning Parameters, and , in: The 1st Workshop on Soft Computing, Dept. of Information Electronics Nagoya University, 1996 |
|
O
| Optimal Parameterization of Point Distribution Models, and , Idiap-RR-01-1998 |
|
| Optimal Setting of Weights, Learning Rate, and Gain, and , Idiap-RR-04-1997 |
|
| Optimization of high order perceptrons, , École Polytechnique Fédérale de Lausanne, 1997 |
|
P
| Pruning of Neural Networks, and , Idiap-RR-03-1997 |
|
R
| Results on the Steepness in Backpropagation Neural Networks, , and , in: Proceedings of the '94 SIPAR-Workshop on Parallel and Distributed Computing, SI Group for Parallel Systems, 1994 |
S
| Segmentation of X-ray Image Sequences Showing the Vocal Tract, , Idiap-RR-01-1999 |
|
| Segmentation of X-ray Image Sequences Showing the Vocal Tract (with tool documentation), , Idiap-RR-01-1999 |
|
| Sparse Initial Topologies for High Order Perceptrons, , and , in: Proceedings of the International Conference on Neural Networks, IEEE, 1996 |
| Superceptron Construction, , and , in: Proceedings of the '96 SIPAR-Workshop on Parallel and Distributed Computing, Scientific and Parallel Computing Group, University of Geneva, Geneva, Switzerland, 1996 |
T
| The 3-regular nets with 4 and 6 vertices per unit cell, , and , in: Zeitschrift fur Kristallographie, 212, 1997 |
| The Interchangeability of Learning Rate and Gain in Backpropagation Neural Networks, , and , in: Neural Computation, 8(02), 1996 |
|
| Tracking Articulators in X-ray Movies of the Vocal Tract, , in: 8th Int. Conf. Computer Analysis of Images and Patterns, Springer Verlag, 1999 |
|
| Two neural network construction methods, and , in: Neural Processing Letters, 6(01), 1997 |
W
| Weight Initialization for High Order and Multilayer Perceptrons, and , in: Proceedings of the '94 SIPAR--Workshop on Parallel and Distributed Computing, SI Group for Parallel Systems, 1994 |
Z
| Zeolite cycle sequences, and , in: Zeolites, 19, 1997 |