Work

Object detection algorithm for unmanned surface vehicle using faster R-CNN

Year: 2018

Type: conference-paper

Abstract: The purpose of this research is development of vision-based object detection algorithm that recognizes a marine object, localizes the object on captured frames, and estimates the distance to the object. Faster R-CNN and stereo vision based depth estimation are combined for real-time marine object detection. The performance of this algorithm is verified by model ship detection test in towing tank. The test results showed that this algorithm is potentially applicable to real USV.

Source: Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)

Authors: Heesu Kim, Evangelos Boulougouris, Sang‐Hyun Kim

Institution: Inha University

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2897914364

FWCI: 0.147

Cites: 14

Cited by: 5

Related to: 10