Abstract: In unsupervised medical image registration, encoder-decoder architectures are widely used to predict dense, full-resolution displacement fields from paired images. Despite their popularity, ...
Abstract: Developing deep learning models for accurate segmentation of biomedical CT images is challenging due to their complex structures, anatomy variations, noise, and unavailability of sufficient ...
XDA Developers on MSN
6 local LLMs I've used that prove they're not just smaller versions of cloud models
These local LLMs are changing the game in lots of fun ways.
Abstract: Image restoration is a long-standing low-level vision problem, e.g., deblurring and deraining. In the process of image restoration, it is necessary to consider not only the spatial details ...
Badrinarayanan, V., Kendall, A. and Cipolla, R. (2015) SegNet A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation. arXiv 1511.00561.
A PNG hiding a prompt injection could steal your repo's secrets, researchers demonstrate. The technique, dubbed 'Ghostcommit, ...
Breast ultrasound interpretation requires simultaneous lesion segmentation and tissue classification, yet conventional multi-task learning approaches suffer from task interference and rigid ...
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