Results 121 to 130 of about 417 (152)
A wavelet-integrated framework for feature extraction and background refinement in hyperspectral anomaly detection. [PDF]
Sci RepKüçük F.
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Artificial Intelligence in Pancreatic Image Analysis: A Review. [PDF]
Sensors (Basel)Liu W, Zhang B, Liu T, Jiang J, Liu Y.
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Fast Multiscale Superpixel Segmentation for SAR Imagery
IEEE Geoscience and Remote Sensing Letters, 2022, Deliang Xiang
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Multiscale-Superpixel-Based SparseCEM for Hyperspectral Target Detection
IEEE Geoscience and Remote Sensing Letters, 2022Jointly exploiting spectral information and spatial information, rather than working on individual pixels, is important for hyperspectral target detection. In this letter, we propose a hyperspectral target detection method relying on superpixel structures of the input image.
Tiande Gao, , Min Zhao
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Multiscale Superpixel-Based Active Learning for Hyperspectral Image Classification
IEEE Geoscience and Remote Sensing Letters, 2022This letter proposes a novel active learning (AL) framework that utilizes the information derived from multiscale superpixel maps for the classification of hyperspectral image. Considering that the nearby pixels with similar spectral properties tend to belong to the same class, we introduce the multiscale superpixel maps for the automatic labeling of ...
Qikai Lu, Lifei Wei
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Multiscale superpixel method for segmentation of breast ultrasound
Computers in Biology and Medicine, 2020In medical diagnostics, breast ultrasound is an inexpensive and flexible imaging modality. The segmentation of breast ultrasounds to identify tumour regions is a challenging and complex task. The major problems of effective tumour identification are speckle noise, artefacts and low contrast.
Ademola Enitan Ilesanmi +2 more
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IEEE Transactions on Geoscience and Remote Sensing, 2019 In virtue of the spatial structural characteristic of surface materials, the performance of the hyperspectral image classification can be boosted by incorporating texture information. Normally, the spatial structure can be extracted by predefined operators, including the popular extended multiattribute profiles (EMAPs) and the Gabor filters.
, Jiasong Zhu, Sen Jia
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PolSAR Image Classification With Multiscale Superpixel-Based Graph Convolutional Network
IEEE Transactions on Geoscience and Remote Sensing, 2022Convolutional neural networks (CNNs) have demonstrated impressive ability to achieve promising results in PolSAR image classification. However, the traditional CNN performs convolution on local square regions with fixed sizes. The selection of these local square regions (patches) cannot fully take advantage of the boundary information of land covers ...
Jianda Cheng +4 more
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Fusion multiscale superpixel features for classification of hyperspectral images
2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016A novel multiscale superpixel-based fusion classification approach is proposed for hyperspectral images in this study. Superpixels are considered as basic processing unit for spectral-spatial based classification. The proposed technique consists of three steps.
X Jia
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Human body segmentation in a static image with multiscale superpixels
2011 3rd International Conference on Awareness Science and Technology (iCAST), 2011In this work, we propose a new method for human body accurate detection in a static image with multiscale superpixels. The main contribution of this work is as follows: (1) A new framework for human body accurate detection using multiscale superpixels and classifier with autothreshold is proposed. (2) Some effective constraints for human body detection
Meng Yao, Huchuan Lu
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