Work

Applicability Analysis Of VGGNET Based Transfer Learning For Oil Spill Classification On SAR Data

Year: 2021

Type: article

Abstract: Oil Spill detection serves a significant application of marine pollution monitoring. Timely rescue in case of ocean oil spills due to accidents or vessel discharges is very important for the marine ecosystem. This paper discusses the experiment done in this line using VGGNet based transfer learning. The input to the proposed system is decomposed polarimetric Synthetic Aperture Radar data. The decomposition is done through ESA PolSARpro 5.1. The paper discusses the analysis of empirical study of transfer learning based VGGNet for classification of oil spill on ocean surface.

Source: Turkish Journal of Computer and Mathematics Education (TURCOMAT)

DOI: 10.17762/turcomat.v12i7.2952

Author: Naishadh Mehta

Language: English

Topic: Oil Spill Detection and Mitigation

Subfield: Pollution

Field: Environmental Science

Domain: Physical Sciences

SDG: Life below water

Open Access status: diamond

OpenAlex ID: W3159986169

FWCI: 0.062

Cites: 4

Cited by: 1

Related to: 10