Choosing an Optimal Neural Network Size to aid a Search Through a Large Image Database

In this paper a fast method of selecting a neural network architecture for pattern recognition tasks is presented. We demonstrate that our proposed method of selecting both input features and hidden neurons avoids the pitfalls exhibited by other methods reported in the literature. It is also shown that the resulting network architecture is extremely lean while at the same time significantly improving the network performance. The resulting solution provides a very useful tool which is now being incorporated in the operations system used for large image database surveys.

• Type: Conference
• Year: 1998
• Where: BMVC
• Authors: Kieron Messer, Josef Kittler
• Keywords: BMVC 1998, Computer Vision, Network Architecture, Neural Network Architecture, Pattern Recognition Tasks