Results 121 to 130 of about 5,165 (221)

Corrosion defect segmentation method based on superpixel feature cascade

Ain Shams Engineering Journal
To solve the segmentation problem caused by the small number of feature points and the change of image brightness on the surface of the storage tank, a corrosion defect segmentation method based on the superpixel feature cascade is proposed in this paper.
Lingyu Sun, Yang Li, Xinbao Li, Chengyan Liu   +3 more
doaj   +1 more source

Joint superpixel and Transformer for high resolution remote sensing image classification

Scientific Reports
Deep neural networks combined with superpixel segmentation have proven to be superior to high-resolution remote sensing image (HRI) classification. Currently, most HRI classification methods that combine deep learning and superpixel segmentation use ...
Guangpu Dang, Zhongan Mao, Tingyu Zhang, Tao Liu, Tao Wang, Liangzhi Li, Yu Gao, Runqing Tian, Kun Wang, Ling Han   +9 more
doaj   +1 more source

Unsupervised instance segmentation with superpixels

Pattern Recognition
Instance 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

Learning contextual superpixel similarity for consistent image segmentation

, 2019
International audienceThis paper addresses the problem of image segmentation by iterative region aggregations starting from an initial superpixel decomposition.
Chaibou Salaou, Mahaman Sani, Mahjoub, Mohamed Ali, Solaiman, Basel, Kalti, Karim, Conze, Pierre-Henri   +4 more
core   +1 more source

Computer Vision with a Superpixelation Camera

CoRR
Conventional cameras generate a lot of data that can be challenging to process in resource-constrained applications. Usually, cameras generate data streams on the order of the number of pixels in the image. However, most of this captured data is redundant for many downstream computer vision algorithms.
Sasidharan Mahalingam, Rachel Brown, Atul Ingle   +2 more
openaire   +2 more sources

Superpixel Salient Object Detection

Salient object detection (SOD) is a core problem in computer vision that involves identifying and segmenting the most visually prominent regions in an image.
Park, Jinman
core  

Adaptive high-precision superpixel segmentation

, 2019
Adaptive high-precision superpixel ...
G Xie (11832605), X Xie (7794023), L Cui (6848960), X Xu (7070408)   +3 more
core  

Medial Features for Superpixel Segmentation. [PDF]

, 2009
Image segmentation plays an important role in computer vision and human scene perception. Image oversegmentation is a common technique to overcome the problem of managing the high number of pixels and the reasoning among them. Specifically, a local and coherent cluster that contains a statistically homogeneous region is denoted as a superpixel. In this
Engel, D., Spinello, L., Triebel, R., Siegwart, R., Bülthoff, H., Curio, C.   +5 more
openaire   +1 more source

Superpixel Segmentation Systems: Design and Analysis

, 2019
Image segmentation is a partitioning of an image into distinct groups of pixels (“regions”), each region preferably spatially connected, where each region ideally corresponds to an object or other semantically meaningful scene component.
Malladi, Sree Ramya Surya Prabha
core  

Spherical Superpixel Segmentation with Context Identity and Contour Intensity

Superpixel segmentation is a popular preprocessing tool in the field of image processing. Nevertheless, conventional planar superpixel generation algorithms are inadequately suited for segmenting symmetrical spherical images due to the distinctive ...
Baolong Guo, Fangliang He, Nannan Liao, Cheng Li, Hui Liu, Wenxing Li   +5 more
core   +1 more source