UEMNet: A Lightweight General-Purpose Convolutional Neural Network for Environmental Applications

Thomas Wang Wei Hong, Ningchang Gan

Keywords: Computer vision, Artificial intelligence, Convolutional Neural Networks, Environmental monitoring, Semantic segmentation

TL;DR: This study introduces a new Convolutional Neural Network (CNN) that is simple in design, lightweight in terms of model parameters, yet able to outperform similar models with similar complexity in theory for adoption by environmental researchers.

Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.

Submission Number: 99