Sep 8, 2020 · Our W-Net model is trained to simultaneously segment images and reconstruct, or predict, the colour of the input images from intermediate representations.
Our W-Net model is trained to simultaneously segment images and reconstruct (or predict) the color of the input images from intermediate representa- tions.
Our W‐Net model is trained to simultaneously segment images and reconstruct, or predict, the colour of the input images from intermediate representations.
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Semantic segmentation and colorization of grayscale aerial imagery with W‐Net models. M Dias, J Monteiro, J Estima, J Silva, B Martins. Expert systems 37 (6) ...
Joel Silva's 3 research works with 50 citations, including: Semantic segmentation and colorization of grayscale aerial imagery with W‐Net models.
Semantic segmentation and colorization of grayscale aerial imagery with <scp>W‐Net</scp> models. Maria Dias, João Monteiro, Jacinto Estima, Joel Silva, Bruno ...
Oct 1, 2022 · The colorization of grayscale images can, nowadays, take advantage of recent progress and the automation of deep-learning techniques.
This paper adopts a unique deep learning-based perspective to review the latest progress in image colorization techniques systematically and comprehensively.
Apr 25, 2024 · Semantic segmentation and colorization of grayscale aerial imagery with W-Net models. Expert Syst. J. Knowl. Eng. 37(6) (2020). [j4]. view.
In this work, we successfully segmented an archive of historical aerial imagery of Antarctica using a U-net-shaped neural network.