Hierarchical feed-forward network for object detection tasks

Bax I, Heidemann G, Ritter H (2006)
Optical Engineering 45(6).

Journal Article | Published | English

No fulltext has been uploaded

Author
; ;
Abstract
Recent research on neocognitron-like neural feed-forward architectures, which have formerly been successfully applied to the recognition of artificial stimuli such as paperclip objects, now also opens up application to more natural stimuli. Such networks exhibit high-recognition performance with respect to translation, rotation, scaling and cluttered surroundings. In this contribution, we introduce a new type of hierarchical model, which is trained using a non-negative matrix factorization algorithm. In contrast to previous work, our approach cannot only classify objects but is also capable of rapid object detection in natural scenes. Thus, the time-consuming and conceptually unsatisfying split-up into a localization stage (e.g., using segmentation) and a subsequent classification can be avoided. The network consists of alternating layers of simple and complex cell planes and incorporates nonlinear processing schemes that have been proposed in recent literature. Learning of receptive field profiles for the lower layers of the network takes place by unsupervised learning whereas a final classification layer is trained supervised. This final layer is then utilized for detection. We test the classification performance of the network on images of natural objects which are systematically distorted. To test the ability to detect objects, cluttered natural background is used. (c) 2006 Society of Photo-Optical Instrumentation Engineers.
Publishing Year
ISSN
PUB-ID

Cite this

Bax I, Heidemann G, Ritter H. Hierarchical feed-forward network for object detection tasks. Optical Engineering. 2006;45(6).
Bax, I., Heidemann, G., & Ritter, H. (2006). Hierarchical feed-forward network for object detection tasks. Optical Engineering, 45(6).
Bax, I., Heidemann, G., and Ritter, H. (2006). Hierarchical feed-forward network for object detection tasks. Optical Engineering 45.
Bax, I., Heidemann, G., & Ritter, H., 2006. Hierarchical feed-forward network for object detection tasks. Optical Engineering, 45(6).
I. Bax, G. Heidemann, and H. Ritter, “Hierarchical feed-forward network for object detection tasks”, Optical Engineering, vol. 45, 2006.
Bax, I., Heidemann, G., Ritter, H.: Hierarchical feed-forward network for object detection tasks. Optical Engineering. 45, (2006).
Bax, Ingo, Heidemann, Gunther, and Ritter, Helge. “Hierarchical feed-forward network for object detection tasks”. Optical Engineering 45.6 (2006).
This data publication is cited in the following publications:
This publication cites the following data publications:

Export

0 Marked Publications

Open Data PUB

Web of Science

View record in Web of Science®

Search this title in

Google Scholar