Classification (TF-Cls) 'Clear', 'Closed', 'Broken', 'Blur' 6,247 3632 × 2760 4,687:561:999(75%:9%:16%) Object Detection (TF-Det) Inside, Middle, Outside Rings 4,736 ...
Abstract: This paper presents a Pseudo-Multi-Task Segmentation Neural Network (PMTNet) for cropland mapping in mountainous regions using high-resolution remote sensing images. PMTNet extends BsiNet by ...
ABSTRACT: Aiming at the problems of intensity inhomogeneity, boundary blurring and noise interference in the segmentation of three-dimensional volume data (such as medical images and industrial CT ...
Most robot headlines follow a familiar script: a machine masters one narrow trick in a controlled lab, then comes the bold promise that everything is about to change. I usually tune those stories out.
Artificial intelligence systems demonstrate strong diagnostic and planning performance in neuro-oncologic radiotherapy, though approximately one-quarter of AI-generated plans require manual clinician ...
This study aims to investigate the application of visual information processing mechanisms in the segmentation of stem cell (SC) images. The cognitive principles underlying visual information ...
According to Fei-Fei Li on Twitter, a groundbreaking large-scale demonstration dataset has been released, featuring 50 distinct tasks and 10,000 demonstrations totaling approximately 1,200 hours of ...
With today's advanced microscopes, scientists can capture videos of entire embryos developing in real time. But there's a catch: turning those breathtaking images into clean, accurate trajectories of ...
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