Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
[1] Image compression techniques survey Abir Jaafar, Ali Al-Fayadh, Naeem Radi Hussain. (2018). Image compression techniques: A survey in lossless and lossy ...
With what appears to be an extra finger on his right hand and no actual arrow in his bow, the man featured in the Department of Energy and Environmental Protection‘s Facebook post did not look like ...
This repository explores finetuning DINOv3 (Siméoni et al., 2025) or DINOv2 (Oquab et al., 2024) encoder weights using Low-Rank Adaptation (Hu et al., 2021) (LoRA) and a simple 1x1 convolution decoder ...
Abstract: Image segmentation is crucial in many fields, but existing image segmentation models based on encoder-decoder networks are constrained by manual parameter tuning and the limited ...
Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for ...
Purpose: Brain tumor segmentation with MRI is a challenging task, traditionally relying on manual delineation of regions-of-interest across multiple imaging sequences. However, this data-intensive ...
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