IEEE

Spectral Structure-Aware Initialization and Probability-Consistent Self-Training for Cross-Scene Hyperspectral Image Classification

Abstract: Cross-scene classification of hyperspectral images (HSIs) aims to classify target domain (TD) data using only labeled source domain (SD) data and unlabeled TD data during training. However, ...
IEEE

FAHM: Frequency-Aware Hierarchical Mamba for Hyperspectral Image Classification

Convolutional neural networks and Transformers have garnered substantial attention in hyperspectral image (HSI) classification, and recently Mamba has made significant progress in modeling long ...
GitHub

unconv-ai/Un-0

Un-0 is an image-generation model built on Kuramoto dynamics: it generates an image by integrating the phase dynamics of a population of coupled oscillators — no diffusion schedule, no adversary, no ...
GitHub

README.md

MotionEdit is a novel dataset and benchmark for motion-centric image editing. We also propose MotionNFT (Motion-guided Negative-aware FineTuning), a post-training framework with motion alignment ...
Frontiers

Label tree semantic losses for rich multi-class medical image segmentation

Rich and accurate medical image segmentation is poised to underpin the next generation of AI-defined clinical practice by delineating critical anatomy for pre-operative planning, guiding real-time ...