Results 21 to 30 of about 18,058 (162)

Multi-temporal Hyperspectral Anomaly Change Detection Based on Dual Space Conjugate Autoencoder [PDF]

Jisuanji kexue, 2023
Hyperspectral anomaly change detection can find anomaly changes from multi-temporal hyperspectral remote sensing images.These anomaly changes are rare,different from the overall background change trend,difficult to be found,but very intere-sting.For the ...
LI Shasha, XING Hongjie, LI Gang
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Spatial Coordinates Correction Based on Multi-Sensor Low-Altitude Remote Sensing Image Registration for Monitoring Forest Dynamics

IEEE Access, 2020
Tree species diversity plays a significant role in our ecosystem. In order to monitor forest dynamics, hyperspectral remote sensing equipped on a small unmanned aerial vehicle (UAV) is commonly applied, such as individual tree detection and ...
Rui Yu, Minghao Lyu, Jiahui Lu, Yang Yang, Guochun Shen, Fei Li   +5 more
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A Hyperspectral Image Classification Method Using Multifeature Vectors and Optimized KELM

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
To improve the accuracy and generalization ability of hyperspectral image classification, a feature extraction method integrating principal component analysis (PCA) and local binary pattern (LBP) is developed for hyperspectral images in this article. The
Huayue Chen, Fang Miao, Yijia Chen, Yijun Xiong, Tao Chen   +4 more
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Network Collaborative Pruning Method for Hyperspectral Image Classification Based on Evolutionary Multi-Task Optimization

Remote Sensing, 2023
Neural network models for hyperspectral images classification are complex and therefore difficult to deploy directly onto mobile platforms. Neural network model compression methods can effectively optimize the storage space and inference time of the ...
Yu Lei, Dayu Wang, Shenghui Yang, Jiao Shi, Dayong Tian, Lingtong Min   +5 more
doaj   +1 more source

In vivo hyperspectral imaging of skin malignant and benign tumors in visible spectrum

Journal of Biomedical Photonics & Engineering, 2018
The paper presents analysis of hyperspectral images for human skin cancer pathologies diagnostics. Hyperspectral images data contained backscattered spectra of normal skin and tumors. Analysis of hyperspectral images provided information about hemoglobin
Ivan A. Bratchenko, Violetta P. Sherendak, Oleg O. Myakinin, Dmitry N. Artemyev, Alexander A. Moryatov, Ekaterina Borisova, Latchezar Avramov, Larisa A. Zherdeva, Andrey E. Orlov, Sergey V. Kozlov, Valery P. Zakharov   +10 more
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Target Detection System Design for Domestic Areas in Iran: Case Study in Abadan and Ahvaz, Using Satellite Multi-spectral Images of Landsat 8 and Sentinel 2 [PDF]

فناوری در مهندسی هوافضا, 2020
Hyperspectral images provide worthful spectral information for target detection. Since these images are not available in Iran, we use multi-spectral images with approximately 10 bands.
Maryam Imani
doaj  

TRANSFER LEARNING WITH LIMITED SAMPLES FOR THE SAME SOURCE HYPERSPECTRAL REMOTE SENSING IMAGES CLASSIFICATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022
A classification method for hyperspectral datasets with a limited number of samples based on transferred convolutional neural network (CNN) is proposed. For the CNN model, a lot of labeled samples are needed for the classification of hyperspectral images,
W. Li, Q. Liu, Y. Wang, H. Li
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MORPHOLOGICAL SEGMENTATION OF HYPERSPECTRAL IMAGES

Image Analysis & Stereology, 2011
The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted
Noyel, Guillaume, Angulo, Jesus, Jeulin, Dominique   +2 more
openaire   +7 more sources

Harmonizing ground and UAV hyperspectral data: A novel spectral correction method for maximizing estimation models and datasets of ground hyperspectral

Smart Agricultural Technology
The accurate and effective monitoring of rice nitrogen status using hyperspectral datasets and estimation models is important for precision agriculture and intelligent breeding.
Zhonglin Wang, Pengxin Deng, Kairui Chen, Ying Xiong, Feng Yang, Cheng Wang, Zhixin Li, Biao Li, Yongjian Sun, Zongkui Chen, Zhiyuan Yang, Jun Ma   +11 more
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Cancer cytoplasm segmentation in hyperspectral cell image with data augmentation

Informatics in Medicine Unlocked
Hematoxylin and Eosin (H&E)-stained images are commonly used to detect nuclear or cancerous regions in cells from images captured by a microscope. Identifying cancer cytoplasm is crucial for determining the type of cancer; hence, obtaining accurate ...
Rebeka Sultana, Hibiki Horibe, Tomoaki Murakami, Ikuko Shimizu   +3 more
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