Results 31 to 40 of about 566 (171)
Remote Sensing Image Denoising Based on Gaussian Curvature and Shearlet Transform
IEEE Access, 2023 Model-based image denoising methods are well suited for use as image processors in remote sensing systems such as satellites due to their well-developed mathematical theory and low computational cost, but these methods can often only deal with a single ...
Libo Cheng, Pengyu Chen
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Advanced Intelligent Systems, Volume 5, Issue 11, November 2023., 2023 Expectation‐maximization algorithm generative adversarial network (EMA‐GAN) is proposed to fuse images from different modalities. This is an EM learning framework based on GAN that maximizes the likelihood of fused results and estimates potential variables.
Xiuliang Xi +5 more
wiley +1 more source
Linearized Riesz transform and quasi-monogenic shearlets [PDF]
International Journal of Wavelets, Multiresolution and Information Processing, 2014 The only quadrature operator of order two on L2(ℝ2) which covaries with orthogonal transforms, in particular rotations is (up to the sign) the Riesz transform. This property was used for the construction of monogenic wavelets and curvelets. Recently, shearlets were applied for various signal processing tasks.
Sören Häuser +2 more
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Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey
CAAI Transactions on Intelligence Technology, Volume 8, Issue 3, Page 581-606, September 2023., 2023 Abstract Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting new knowledge. By using DL, the extraction of advanced data representations and knowledge can be made possible. Highly effective DL techniques help to find more hidden knowledge.
Mehdi Gheisari +10 more
wiley +1 more source
Otherness feature extraction method for underground image based on Shearlet transform
Gong-kuang zidonghua, 2016 For the problem that face images collected underground are susceptible to dust interference and most feature extraction methods are sensitive to noise, an otherness feature extraction method for underground image based on Shearlet transform was proposed.
HUANG Yu, ZHANG Yingjun, PAN Lihu
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River boundary detection and autonomous cruise for unmanned surface vehicles
IET Image Processing, Volume 17, Issue 11, Page 3196-3215, 18 September 2023., 2023 The detection of river boundaries is important for judging the drivable area of USVs, and it can also be utilized to ensure driving safety by limiting the effective drivable areas of the USVs in the river areas. This work proposes a real‐time detection method for river boundaries based on a LiDAR sensor to detect the boundaries of incompletely ...
Kai Zhang +5 more
wiley +1 more source
Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning
Journal of Imaging, 2016 The Gleason grading system is generally used for histological grading of prostate cancer. In this paper, we first introduce using the Shearlet transform and its coefficients as texture features for automatic Gleason grading.
Hadi Rezaeilouyeh, Mohammad H. Mahoor
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GF-3 SAR IMAGE DESPECKLING BASED ON THE IMPROVED NON-LOCAL MEANS USING NON-SUBSAMPLED SHEARLET TRANSFORM [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 GF-3 synthetic aperture radar (SAR) images are rich in information and have obvious sparse features. However, the speckle appears in the GF-3 SAR images due to the coherent imaging system and it hinders the interpretation of images seriously.
R. Shi, Z. Sun
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Use of the Shearlet Transform and Transfer Learning in Offline Handwritten Signature Verification and Recognition [PDF]
Sahand Communications in Mathematical Analysis, 2020 Despite the growing growth of technology, handwritten signature has been selected as the first option between biometrics by users. In this paper, a new methodology for offline handwritten signature verification and recognition based on the Shearlet ...
Atefeh Foroozandeh +2 more
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Image fusion based on shift invariant shearlet transform and stacked sparse autoencoder
Journal of Algorithms & Computational Technology, 2018 Stacked sparse autoencoder is an efficient unsupervised feature extraction method, which has excellent ability in representation of complex data. Besides, shift invariant shearlet transform is a state-of-the-art multiscale decomposition tool, which is ...
Peng-Fei Wang +3 more
doaj +1 more source