A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Chunming Li, Chenyang Xu, Changfeng Gui, et al.
Proposes a variational level set formulation with a distance regularization term that eliminates the need for reinitialization, enabling stable and efficient image segmentation.
Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li, et al.
The LiTS benchmark evaluates liver and tumor segmentation algorithms on a diverse CT dataset, finding no single algorithm excels at both tasks and highlighting the need for improved tumor detection.
Felix Gremse, Marius Stärk, Josef Ehling, et al.
A GPU-accelerated software tool for interactive segmentation and rendering of multimodal biomedical volume data.
Konstantinos Kamnitsas, Christian Ledig, Virginia Newcombe, et al.
A dual-pathway 3D CNN with dense training and fully connected CRF achieves state-of-the-art brain lesion segmentation across multiple pathologies.
Evan Shelhamer, Jonathan Long, Trevor Darrell
Fully convolutional networks trained end-to-end for semantic segmentation achieve state-of-the-art results by adapting classification nets and using a skip architecture for detailed predictions.
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, et al.
DeepLab advances semantic segmentation via atrous convolution, ASPP, and fully connected CRFs, achieving state-of-the-art on multiple benchmarks.
Yuqi Han, Huaping Liu, Yufeng Wang, et al.
A comprehensive review of recent UAV vision techniques for object detection, tracking, and semantic segmentation, highlighting challenges and future directions.
Caroline Pantofaru, Martial Hebert
This paper evaluates mean shift and graph-based segmentation algorithms using the Normalized Probabilistic Rand index for objective comparison.
Ioannis Patras, Ella Hendriks, Reginald L. Lagendijk
This paper proposes a spatio-temporal video segmentation method that labels watershed segments using MAP estimation with a Markov random field model.
Feng Zhao, Xianghua Xie
This paper surveys interactive segmentation techniques for medical images, combining automatic methods with user guidance to improve accuracy and reduce manual effort.
Y. Tsaig, Amir Averbuch
A method for automatic segmentation of moving objects in video sequences using graph labeling over a region adjacency graph with Markov random field optimization.
Kostas Haris, S.N. Efstratiadis, Nicos Maglaveras, et al.
A hybrid image segmentation algorithm combining watersheds and fast region merging via nearest neighbor graph for efficient 2D/3D medical image analysis.