Technology developed by U of T Engineering researchers could help predict wildfire spread to support first responder safety ...
Overview:  Compares the leading computer vision APIs, multimodal AI models, and open-source vision frameworks available in ...
The spatial organization of chromatophore-muscle innervation by motoneurons enables the generation of chromatophore-shaped noise, virtual or composite chromatophores, and shape elements such as lines ...
Celldetective is an open-source software integrating segmentation, tracking, and event detection to perform high-throughput end-to-end study of dynamic cell interactions, without requiring coding ...
I-MedSAM with the fewest trainable params (1.6M) surpasses the state-of-the-art discrete and implicit approaches and exhibits a solid generalization ability when facing data shifts. We propose ...
Abstract: Image segmentation is an application area of computer vision and digital image processing that partitions a digital image into multiple image regions or segments. This process involves ...
We propose MaskCut approach to generate pseudo-masks for multiple objects in an image. CutLER can learn unsupervised object detectors and instance segmentors solely on ImageNet-1K. CutLER exhibits ...
Abstract: Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video ...