Aiming at the problems of intensity inhomogeneity, boundary blurring and noise interference in the segmentation of three-dimensional volume data (such as medical images and industrial CT data). In ...

Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as Faster R-CNN and ...

2025 GIFNet: One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusion CVPR 2025 DCEvo: Discriminative Cross-Dimensional Evolutionary Learning for Infrared and Visible Image ...

This repository includes an enhanced lightweight grid-based ground segmentation algorithm that efficiently separates ground points from obstacle points in 3D point clouds. The algorithm is designed ...

Pore space in tight sandstone formation is very complex with micro-scale and nano-scale pores/throats, the multi-scale characteristics needs to be considered for the construction of microscopic pore ...

Abstract: One-dimensional threshold segmentation algorithm has poor adaptability and poor noise immunity, while two-dimensional threshold segmentation has high computational complexity. To solve these ...

Abstract: Fuzzy c-means algorithm with spatial constraints (FCM_S) is more effective for image segmentation. However, it still lacks enough robustness to noise and outliers, and costs much time in ...