Abstract: Semantic segmentation is one of the fundamental tasks of pixel-level remote sensing image analysis. Currently, most high-performance semantic segmentation methods are trained in a supervised ...

Abstract: Automatic localization of skin lesions within dermoscopy images is a crucial step toward developing a decision support system for skin cancer detection. However, segmentation of the lesion ...

Training a computer vision model on a 50:50 blend of synthetic and real eye images produces more reliable segmentation of the ...

Prion and prion-like proteins are classically associated with protein misfolding, but amyloidogenic sequences can also participate in host defence. Here, using deep learning, we screened 19.3 million ...

New research from FIU shows that some visual-language AI models have become particularly susceptible to image-based hacks.

For the longest time, learning photo editing has gone hand-in-hand with learning photography. But I just came across an ...

To the best of our knowledge, this is the first list of deep learning papers on medical applications. There are couple of lists for deep learning papers in general, or computer vision, for example ...

[Notice] This list is not being maintained anymore because of the overwhelming amount of deep learning papers published every day since 2017. A curated list of the most cited deep learning papers ...

Contributed by J. Anthony Movshon; received March 9, 2022; accepted July 23, 2022; reviewed by Christos Papadimitriou and Qasim Zaidi This contribution is part of the special series of Inaugural ...

Consequently, their segmentation performance often fails to meet the stringent accuracy and robustness requirements of clinical imaging analysis. With the rapid advancement of deep learning, ...