Assessment of Spectral based Solutions for the Detection of Floating Marine Debris

TL;DR

This paper evaluates spectral-based remote sensing methods for detecting floating marine debris using the MARIDA dataset, emphasizing the importance of standardized benchmarks for fair performance comparison.

Contribution

It provides an assessment of spectral solutions for marine debris detection on the MARIDA dataset, highlighting the need for precise references for fair evaluation.

Findings

Spectral methods show potential but require standardized benchmarks.

Current evaluations lack consistent reference points.

MARIDA dataset facilitates fair comparison of detection algorithms.

Abstract

Typically, the detection of marine debris relies on in-situ campaigns that are characterized by huge human effort and limited spatial coverage. Following the need of a rapid solution for the detection of floating plastic, methods based on remote sensing data have been proposed recently. Their main limitation is represented by the lack of a general reference for evaluating performance. Recently, the Marine Debris Archive (MARIDA) has been released as a standard dataset to develop and evaluate Machine Learning (ML) algorithms for detection of Marine Plastic Debris. The MARIDA dataset has been created for simplifying the comparison between detection solutions with the aim of stimulating the research in the field of marine environment preservation. In this work, an assessment of spectral based solutions is proposed by evaluating performance on MARIDA dataset. The outcome highlights the need of precise reference for fair evaluation.