Explore how AI phenotypic screening transforms image-based drug discovery through advanced phenotypic data analysis and ML-driven cell-based assays.

Abstract: Semantic segmentation is one of the fundamental tasks of pixel-level remote sensing image analysis. Currently, most high-performance semantic segmentation methods are trained in a supervised ...

Abstract: Automatic localization of skin lesions within dermoscopy images is a crucial step toward developing a decision support system for skin cancer detection. However, segmentation of the lesion ...

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 ...

Naveen Rao's Unconventional AI has released Un-0, an image generation model running on a simulated oscillator chip architecture it claims could slash power.

Modern medical imaging increasingly relies on artificial intelligence to support detection, diagnosis, and prognostic ...

As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability enables us to be aware of our position in space, judge distances, possess ...

New research from FIU shows that some visual-language AI models have become particularly susceptible to image-based hacks.

Integration of smartphone-based imaging and artificial intelligence (AI)-driven diagnostics provides an effective strategy ...

Deep learning has transformed remote sensing, driving state-of-the-art results in land use and land cover classification, ...

To the best of our knowledge, this is the first list of deep learning papers on medical applications. There are couple of lists for deep learning papers in general, or computer vision, for example ...