Spectra-MobileNet: A Frequency-Aware Ordinal Framework for Fine-Grained Prawn Freshness Assessment

Le résumé fourni par la source

The freshness assessment of prawns has become imperative in the aquaculture industry. Manual methods that were previously used have been found to be highly inconsistent and expensive too. This implies that there is need for a reliable and efficient technique like the automated image classification, which will carry out the process quickly. Researches related to shrimp quality assessment have largely relied on datasets that are inadequate and only focused on visual features that cannot adequately distinguish freshness differences. To overcome the limitations, the developed Spectra-MobileNet technique has been able to apply lightweight design and frequency domain feature extraction to achieve effective freshness recognition. In contrast to conventional Convolutional Neural Networks, which focus solely on spatial attributes, the technique relies on frequency domain images with MobileNetV2 architecture. The applicability of the method is verified via an experiment using the prawn images dataset.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.