DentalSegmentator is based on nnU-Net framework. It has been trained on 470 dento-maxillo-facial CT and CBCT scans, and evaluated on a hold-out test dataset of 256 CT and CBCT scans from 7 ...
In recent years, the rapid development of machine vision based on artificial intelligence (AI) has gained increasing attention in agriculture (Abbasi et al., 2022; Maraveas, 2024). This becomes ...
We host our model on HuggingFace space, feel free to try our UnSAMv2 Demo! UnSAMv2 support granularity control for interactive image segmentation, whole image segmentation, and video segmentation.
For startups and established businesses, understanding the importance of segmentation is essential for the granular analysis of consumer demographics, behaviors, needs, and preferences. These insights ...
Recent developments in materials science have made it possible to synthesize millions of individual nanoparticles on a chip. However, many steps in the characterization process still require extensive ...
Abstract: Segmentation is an important step in medical imaging to acquire qualitative measurements such as the location of the desired objects and also for quantitative measurements such as area, ...
We present LABKIT, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to ...
Mean shift clustering is a centroid-based algorithm effective for unsupervised learning applications. The algorithm shifts data points towards the mean of surrounding points to form clusters. Like ...
We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of 3D microscopy data and applied this to the mouse ...
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