Technologies
Title: | A Novel System for Seafloor Classification Using Artificial Neural Network (ANN) Hybrid Layout with the Use of Unprocessed Multi-Beam Backscatter Data |
Area: | Physical Sciences |
Focus Area: | Seafloor Classification |
Social Benefits: | Combined use of the two variants of the learning vector quantization (LVQ) network to achieve the best classification of the seafloor characteristics, which is a capability that is hitherto non-existent , Self-organization of multi-beam input data vectors into coarse clusters in the output space without any a priori information , Raw dataset can be used as input vectors to the classification network , Reduces computational time overhead |
Developing Agency: | CSIR-National Institute Of Oceanography (NIO), Goa |
Technology Readiness Index: | Technology Demonstration |
Email: | vsnmurty@nio.org |
| Website Link : | http://www.nio.org |
| Source (more info) : | https://t.ly/l_sb |
Brief Description
Description : | The novel system for seafloor classification uses artificial neural network (ANN) hybrid layout with the use of unprocessed multi-beam backscatter data. Its a real-time seafloor roughness classifier using backscatter data after training the self-organized mapping (SOM) network and learning vector quantization (LVQ) network wherein, the system has the unique capability for the combined use of unsupervised SOM followed by supervised LVQ to achieve a highly improved performance in the roughness classification. |