Results 11 to 20 of about 471,167 (221)

Superpixel Segmentation With Fully Convolutional Networks [PDF]

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
In computer vision, superpixels have been widely used as an effective way to reduce the number of image primitives for subsequent processing. But only a few attempts have been made to incorporate them into deep neural networks.
Fengting Yang, Qian Sun, Hailin Jin, Zihan Zhou   +3 more
semanticscholar   +4 more sources

Rethinking Unsupervised Neural Superpixel Segmentation [PDF]

2022 IEEE International Conference on Image Processing (ICIP), 2022
Recently, the concept of unsupervised learning for superpixel segmentation via CNNs has been studied. Essentially, such methods generate superpixels by convolutional neural network (CNN) employed on a single image, and such CNNs are trained without any ...
Moshe Eliasof, Nir Ben Zikri, Eran Treister   +2 more
semanticscholar   +3 more sources

Boundary-preserving superpixel segmentation

Journal of Applied Science and Engineering
In recent years, superpixel segmentation has been widely used in image processing tasks as a preprocessing step. Superpixel segmentation aims to group pixels into homogeneous regions while maintaining edges.
Yuejia Lin, Zhao Li, Chenxun Yuan, Yi Liu   +3 more
doaj   +2 more sources

Detection of Hypergranulation Tissue in Chronic Wound Images Using Artificial Intelligence Algorithms. [PDF]

Wound Repair Regen
ABSTRACT Hypergranulation in chronic wounds reflects impaired healing, leading to delayed recovery, increased risk of infection and higher treatment costs for healthcare systems. Despite its impact, hypergranulation is often misidentified in the early stages, hindering timely intervention. This study presents a deep learning‐based method to distinguish
Reifs D, Casanova L, Reig-Bolaño R, Coda A.   +3 more
europepmc   +2 more sources

Hybrid superpixel segmentation [PDF]

2015 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2015
Superpixel over-segment image into meaningful clusters so that pixels in each cluster belong to one object. Many state-of-art superpixel algorithms have to make trade-offs between different concerns. As a result, algorithms that can produce good result in some situations fail in another.
Yu, Y, Lai, S, Liu, Y, Du, T
openaire   +2 more sources

Artificial Intelligence-Based Approaches for Brain Tumor Segmentation in MRI: A Review. [PDF]

NMR Biomed
Manually segmenting brain tumors in magnetic resonance imaging is a time‐consuming task that requires years of professional experience and clinical expertise. We proposed a study, which contains a comprehensive review of the brain tumor segmentation techniques. It selects the effective approaches to better understand the AI applications for brain tumor
Bibi K, Nawaz M, Khan S, Daud M, Masood A, Abdelgawad MA, Abbasi SMT, Rizwan, Khan A, Yuan W.   +9 more
europepmc   +2 more sources

Lung Field Segmentation in Chest X-ray Images Using Superpixel Resizing and Encoder–Decoder Segmentation Networks

Bioengineering, 2022
Lung segmentation of chest X-ray (CXR) images is a fundamental step in many diagnostic applications. Most lung field segmentation methods reduce the image size to speed up the subsequent processing time.
Chien-Cheng Lee, Edmund Cheung So, Lamin Saidy, Min-Ju Wang   +3 more
doaj   +1 more source

BASS: Boundary-Aware Superpixel Segmentation [PDF]

2016 23rd International Conference on Pattern Recognition (ICPR), 2016
This work is partly funded by the Spanish MINECO project RobInstruct TIN2014-58178-R, by the ERA-Net Chistera project I-DRESS PCIN-2015-147 and by the EU project AEROARMS H2020-ICT-2014-1-644271. A. Rubio is supported by the industrial doctorate grant 2015-DI-010 of the AGAUR.
Rubio, Antonio, Yu, LongLong, Simo-Serra, Edgar, Moreno-Noguer, Francesc   +3 more
openaire   +3 more sources

Superpixel Generation for SAR Imagery Based on Fast DBSCAN Clustering With Edge Penalty

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
In this article, we propose an adaptive superpixel generation algorithm for synthetic aperture radar (SAR) imagery, which is implemented based on fast density-based spatial clustering of applications with noise (DBSCAN) clustering and superpixel merging ...
Liang Zhang, Shengtao Lu, Canbin Hu, Deliang Xiang, Tao Liu, Yi Su   +5 more
doaj   +1 more source

Building Detection in High-Resolution Remote Sensing Images by Enhancing Superpixel Segmentation and Classification Using Deep Learning Approaches

Buildings, 2023
Accurate building detection is a critical task in urban development and digital city mapping. However, current building detection models for high-resolution remote sensing images are still facing challenges due to complex object characteristics and ...
Ayoub Benchabana, M. Kholladi, Ramla Bensaci, Belal Khaldi   +3 more
semanticscholar   +1 more source