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Relevant bibliographies by topics / SUPER-SIFT APPROACH

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Academic literature on the topic 'SUPER-SIFT APPROACH'

Author: Grafiati

Published: 11 September 2023

Last updated: 31 July 2025

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Journal articles on the topic "SUPER-SIFT APPROACH"

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Li, Xiao Qin, and Kang Ling Fang. "Super-Resolution by POCS-SIFT Approach." Applied Mechanics and Materials 519-520 (February 2014): 562–67. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.562.

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Projection Onto Convex Sets theory (POCS) and Scale Invariant Feature Transform (SIFT) algorithm were introduced for super-resolution restoration of moving blurred image. In order to achieve a better restored image, a POCS-SIFT based super-resolution image restoration algorithm was proposed, which incorporates POCS theory and SIFT algorithm. From experimental results, the improved restored images are obtained by POCS-SIFT hybrid algorithm.

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Rajalakshmi, C., Al M. Germanus, and R. Balasubramanian. "Copy move forgery detection using key point localized super pixel based on texture features." Computer Optics 43, no. 2 (2019): 270–76. http://dx.doi.org/10.18287/2412-6179-2019-43-2-270-276.

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The most important barrier in the image forensic is to ensue a forgery detection method such can detect the copied region which sustains rotation, scaling reflection, compressing or all. Traditional SIFT method is not good enough to yield good result. Matching accuracy is not good. In order to improve the accuracy in copy move forgery detection, this paper suggests a forgery detection method especially for copy move attack using Key Point Localized Super Pixel (KLSP). The proposed approach harmonizes both Super Pixel Segmentation using Lazy Random Walk (LRW) and Scale Invariant Feature Transfo

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Chakravarthy, Munipally. "Enhancing Fingerprint Image Resolution Using Auto Encoder and Interpolation Techniques." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem49200.

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Abstract - Abstract: This study introduces an efficient super-resolution (SR) method for enhancing low-resolution fingerprint images using an autoencoder combined with spline and bicubic interpolation techniques. The approach upscales images from 129×97 to 258×194 while preserving fine details and minimizing artifacts. Trained on the FVC 2004 dataset and tested on both FVC 2004 and FVC 2002, the model achieves strong performance with SSIM of 0.968, PSNR of 35.14, and MSE of 0.007. It also attains 100% identification accuracy using the SIFT algorithm, demonstrating its effectiveness for biometr

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Amintoosi, M., M. Fathy, and N. Mozayani. "A fast image registration approach based on SIFT key-points applied to super-resolution." Imaging Science Journal 60, no. 4 (2012): 185–201. http://dx.doi.org/10.1179/1743131x11y.0000000015.

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Liu, Xiaoming, Yan Yang, Yuanhong Zhong, Dong Xiong, and Zhiyong Huang. "Super-Pixel Guided Low-Light Images Enhancement with Features Restoration." Sensors 22, no. 10 (2022): 3667. http://dx.doi.org/10.3390/s22103667.

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Dealing with low-light images is a challenging problem in the image processing field. A mature low-light enhancement technology will not only be conductive to human visual perception but also lay a solid foundation for the subsequent high-level tasks, such as target detection and image classification. In order to balance the visual effect of the image and the contribution of the subsequent task, this paper proposes utilizing shallow Convolutional Neural Networks (CNNs) as the priori image processing to restore the necessary image feature information, which is followed by super-pixel image segm

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Fang, Bosheng, Siyuan Jiao, Chengming Wang, and Qianyu Yin. "Research on Methods of Micro-target Detection in Various Application Scenarios." Highlights in Science, Engineering and Technology 94 (April 26, 2024): 452–60. http://dx.doi.org/10.54097/vc5hsv26.

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This paper provides a comprehensive introduction and comparison of the research on small target detection algorithms in different application scenarios and systematically explores the application of deep learning algorithms for small target detection in remote sensing imagery, visible imagery, and infrared imagery. In remote sensing images, the Deconvolution R-CNN algorithm is used to improve the accuracy of small target detection by adding a deconvolution layer. In the field of visible images, a Gaussian Mixture Model (GMM)-based approach is introduced to achieve fast detection of small targe

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Taveira, Rodney. "Don DeLillo, 9/11 and the Remains of Fresh Kills." M/C Journal 13, no. 4 (2010). http://dx.doi.org/10.5204/mcj.281.

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It’s a portrait of grief, to be sure, but it puts grief in the air, as a cultural atmospheric, without giving us anything to mourn.—— Tom Junod, “The Man Who Invented 9/11”The nearly decade-long attempt by families of 9/11 victims to reclaim the remains of their relatives involves rhetorics of bodilessness, waste, and virtuality that offer startling illustrations of what might be termed “the poetics of grief.” After combining as the WTC Families for Proper Burial Inc. in 2002, the families sued the city of New York in 2005. They lost and the case has been under appeal since 2008. WTC Families

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Dissertations / Theses on the topic "SUPER-SIFT APPROACH"

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DEEPAK. "A SUPER-SIFT APPROACH FOR COPY-MOVE FORGERY DETECTION." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15910.

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Today’s technological era is described by the outspread of digital images. They are the most ordinary formation of conveying information whether through newspapers, internet, books, magazine, scientific journals or social media. They are used as a powerful proof against various crimes, frauds and as an evidence in various situations. With the evolution of image processing in past few years and many other image editing software, capturing, creating or altering images according to our perspective has become very simple and available. There are several kinds of image tampering like copy-mov

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