Search Results for author:
Found 5 papers, 3 papers with code
Overhead Line Defect Recognition Based on Unsupervised Semantic Segmentation
Overhead line inspection greatly benefits from defect recognition using visible light imagery.
Tree-GPT: Modular Large Language Model Expert System for Forest Remote Sensing Image Understanding and Interactive Analysis
This empowers LLMs with the ability to comprehend images, acquire accurate knowledge, generate code, and perform data analysis in a local environment.
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic Segmentation
Understanding indoor scenes is crucial for urban studies.
Ranked #1 on
Real-Time Semantic Segmentation
on NYU Depth v2
Self-Supervised Blind Motion Deblurring With Deep Expectation Maximization
In contrast, this paper presents a dataset-free deep learning method for removing uniform and non-uniform blur effects from images of static scenes.
Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics
While supervised deep learning has been a prominent tool for solving many image restoration problems, there is an increasing interest on studying self-supervised or un- supervised methods to address the challenges and costs of collecting truth images.
