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: Unsupervised domain adaptation (UDA) techniques are vital for semantic segmentation in geosciences, effectively utilizing remote sensing imagery across diverse domains. However, most ...

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 ...

It may look like a picture of a panda bear to you, but to your business's AI agent, it can act like a skeleton key, bypassing safety safeguards and potentially causing the model to generate harmful, ...

AI. Is there reason to worry? A new experiment tests how gen-AI imagery can affect how people feel about their bodies.

A new airborne imaging approach can reliably detect unexploded weapons that lie in shallow coastal waters and remain an ...

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

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

As enterprises rapidly embrace multimodal AI capable of understanding both text and images, security researchers are discovering that these powerful new capabilities introduce equally sophisticated ...

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

This repo is used for recording, tracking, and benchmarking several recent transformer-based visual segmentation methods, as a supplement to our survey. If you find any work missing or have any ...