Results 81 to 90 of about 3,488 (207)
Accelerated superpixel image segmentation with a parallelized DBSCAN algorithm
, 2022 Segmentation of an image into superpixel clusters is a necessary part of many imaging pathways. In this article, we describe a new routine for superpixel image segmentation (F-DBSCAN) based on the DBSCAN algorithm that is six times faster than previous ...
MacDonald, Bruce A +3 more
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IET Image Processing, Volume 20, Issue 1, January/December 2026.This study proposes a Gated and Cross‐Dynamically Enhanced Network (GCD‐Net) for accurate extraction of offshore raft aquaculture from Sentinel‐2 imagery. GCD‐Net integrates novel gated residual blocks, cross‐guided attention, and dynamic attention ASPP modules to enhance feature representation and boundary precision.
Yu Wang +4 more
wiley +1 more source
Content-driven superpixels and their applications
, 2013 This thesis develops a new superpixel algorithm that displays excellent visual reconstruction of the original image. It achieves high stability across multiple random initialisations, achieved by producing superpixels directly corresponding to local ...
Lowe, Richard
core
Semantic-Aware Superpixel for Weakly Supervised Semantic Segmentation
, 2023 Weakly-supervised semantic segmentation aims to train a semantic segmentation network using weak labels. Among weak labels, image-level label has been the most popular choice due to its simplicity.
Park, Daeyoung +2 more
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An Object-Aware Network Embedding Deep Superpixel for Semantic Segmentation of Remote Sensing Images
Remote SensingSemantic segmentation forms the foundation for understanding very high resolution (VHR) remote sensing images, with extensive demand and practical application value.
Ziran Ye +5 more
doaj +1 more source
Superpixel Segmentation: An Evaluation
, 2015 In recent years, superpixel algorithms have become a standard tool in computer vision and many approaches have been proposed. However, different evaluation methodologies make direct comparison difficult. We address this shortcoming with a thorough and fair comparison of thirteen state-of-the-art superpixel algorithms.
openaire +1 more source
Unsupervised instance segmentation with superpixels
Pattern RecognitionInstance segmentation is essential for numerous computer vision applications, including robotics, human-computer interaction, and autonomous driving. Currently, popular models bring impressive performance in instance segmentation by training with a large number of human annotations, which are costly to collect.
openaire +2 more sources
International Journal of Forestry Research, Volume 2026, Issue 1, 2026.Trees outside forests (TOFs) represent an important natural and anthropogenic resource that contributes significantly to biodiversity conservation, climate resilience, and the protection of forest genetic resources (FGRs). Despite their ecological and socioeconomic importance, TOFs are increasingly declining due to land‐use changes, urbanization ...
Aman Dabral +9 more
wiley +1 more source
A Novel RGBD Image Superpixel Segmentation Intergrated Depth Map Quality
, 2022 Part 8: Image ProcessingInternational audienceSuperpixel segmentation is to gather adjacent pixels into sub-regions with certain semantics, which can greatly reduce the computational complexity of subsequent image processing.
Tao, Hong, Wei, Weiyi, Chen, Wenxia
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IET Image ProcessingThe fuzzy C‐means clustering (FCM) algorithm is widely used in greyscale and colour image segmentation, especially in real colour images. However, in the process of interested regions extraction, it performs barely satisfactory due to the use of single ...
Xie Zeyu +3 more
doaj +1 more source