Results 71 to 80 of about 933,413 (267)
Remote Sensing, 2020 Knowledge of forest structures—and of dead wood in particular—is fundamental to understanding, managing, and preserving the biodiversity of our forests.
Peter Krzystek +4 more
doaj +1 more source
UCP-Net: Unstructured Contour Points for Instance Segmentation [PDF]
arXiv, 2021 The goal of interactive segmentation is to assist users in producing segmentation masks as fast and as accurately as possible. Interactions have to be simple and intuitive and the number of interactions required to produce a satisfactory segmentation mask should be as low as possible.
arxiv
RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2016 Recently, very deep convolutional neural networks (CNNs) have shown outstanding performance in object recognition and have also been the first choice for dense classification problems such as semantic segmentation.
Guosheng Lin +3 more
semanticscholar +1 more source
Objective-Dependent Uncertainty Driven Retinal Vessel Segmentation [PDF]
arXiv, 2021 From diagnosing neovascular diseases to detecting white matter lesions, accurate tiny vessel segmentation in fundus images is critical. Promising results for accurate vessel segmentation have been known. However, their effectiveness in segmenting tiny vessels is still limited.
arxiv
Remote Sensing, 2019 Motivated by the increasing availability of open and free Earth observation data through the Copernicus Sentinel missions, this study investigates the capacity of advanced computational models to automatically generate thematic layers, which in turn ...
Vasileios Syrris +5 more
doaj +1 more source
New multiple sclerosis lesion segmentation and detection using pre-activation U-Net
Frontiers in Neuroscience, 2022 Automated segmentation of new multiple sclerosis (MS) lesions in 3D MRI data is an essential prerequisite for monitoring and quantifying MS progression. Manual delineation of such lesions is time-consuming and expensive, especially because raters need to
Pooya Ashtari +5 more
doaj +1 more source
Кібернетика та комп'ютерні технології, 2022 Introduction. Many computer vision applications often use procedures for recognizing various shapes and estimating their dimensional characteristics. The entire pipeline of such processing consists of several stages, each of which has no clearly defined ...
Oleksandr Golovin
doaj +1 more source
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image Segmentation [PDF]
arXiv, 2023 The Segment Anything Model (SAM) exhibits a capability to segment a wide array of objects in natural images, serving as a versatile perceptual tool for various downstream image segmentation tasks. In contrast, medical image segmentation tasks often rely on domain-specific knowledge (DSK).
arxiv
, 2022 You should run "main.py". The required input and output functions are in "input_output_function.py" and all the necessary functions for segmentation are in "segmentation.py"
openaire +1 more source
3D Meta-Segmentation Neural Network [PDF]
arXiv, 2021 Though deep learning methods have shown great success in 3D point cloud part segmentation, they generally rely on a large volume of labeled training data, which makes the model suffer from unsatisfied generalization abilities to unseen classes with limited data.
arxiv