Results 1 to 10 of about 15,689 (243)

Multiple Superpixel Graphs Learning Based on Adaptive Multiscale Segmentation for Hyperspectral Image Classification [PDF]

Remote Sensing, 2022
Hyperspectral image classification (HSIC) methods usually require more training samples for better classification performance. However, a large number of labeled samples are difficult to obtain because it is cost- and time-consuming to label an HSI in a ...
Chunhui Zhao, Boao Qin, Shou Feng, Wenxiang Zhu   +3 more
doaj   +2 more sources

SLIC Superpixels Compared to State-of-the-Art Superpixel Methods [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012
Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel algorithm. In an effort to understand the benefits and drawbacks of existing methods, we empirically compare five state-of-the-art superpixel algorithms for their ability to adhere to image boundaries,
Sabine Süsstrunk, Appu Shaji, Kevin Smith   +2 more
exaly   +3 more sources

TSSP-UNet: A Two-Stage Weakly Supervised Pathological Image Segmentation With Point Annotations. [PDF]

IET Syst Biol
Deep convolutional neural networks excel at image segmentation but face challenges with complex instance training and high‐precision annotation acquisition. This study proposes TSSP‐UNet, a two‐stage weakly supervised segmentation approach: the first stage trains a segmentation network with constraint and attention mechanisms plus a feature aggregation
Wang S, Shi G, Wang Y, Li Q, Zhao Y, Cheng X.   +5 more
europepmc   +2 more sources

Multiscale superpixel depth feature extraction for hyperspectral image classification [PDF]

Scientific Reports
Recently, superpixel segmentation has been widely employed in hyperspectral image (HSI) classification of remote sensing. However, the structures of land-covers in HSI commonly vary greatly, which makes it difficult to fully fit the boundaries of land ...
Qi Yan, Shuzhen Zhang, Xiang Chen, Ziyou Zheng   +3 more
doaj   +2 more sources

Color detection of printing based on improved superpixel segmentation algorithm [PDF]

Scientific Reports
We propose an improved superpixel segmentation algorithm based on visual saliency and color entropy for online color detection in printed products. This method addresses the issues of low accuracy and slow speed in detecting color deviations in print ...
Hongwu Zhan, Yuhao Shou, Lidu Wen, Fang Xu, Libin Zhang   +4 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

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

Temporally Consistent Superpixels [PDF]

2013 IEEE International Conference on Computer Vision, 2013
Super pixel algorithms represent a very useful and increasingly popular preprocessing step for a wide range of computer vision applications, as they offer the potential to boost efficiency and effectiveness. In this regards, this paper presents a highly competitive approach for temporally consistent super pixels for video content. The approach is based
Reso M., Jachalsky J., Rosenhahn B., Ostermann J.   +3 more
openaire   +2 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

Dynamic spectral residual superpixels [PDF]

Pattern Recognition, 2021
We consider the problem of segmenting an image into superpixels in the context of $k$-means clustering, in which we wish to decompose an image into local, homogeneous regions corresponding to the underlying objects. Our novel approach builds upon the widely used Simple Linear Iterative Clustering (SLIC), and incorporate a measure of objects' structure ...
Zhang, Jianchao, Aviles-Rivero, Angelica I., Heydecker, Daniel, Zhuang, Xiaosheng, Chan, Raymond, Schönlieb, Carola-Bibiane   +5 more
openaire   +2 more sources