Showing 1 - 20 results of 4,558 for search 'different evaluation algorithm', query time: 0.27s Refine Results
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    Evaluation of different spectral indices for wheat lodging assessment using machine learning algorithms by Shikha Sharda, Sumit Kumar, Raj Setia, Prince Dhiman, N. R. Patel, Brijendra Pateriya, Ali Salem, Ahmed Elbeltagi

    Published 2025-07-01
    “…The temporal characteristics of crop phenology from November 2022 to April 2023 were analyzed for wheat classification. The normalized difference vegetation index (NDVI) was computed during this period followed by implementation of random forest (RF), decision tree (DT), and support vector machine (SVM) algorithms to evaluate their performance for wheat classification. …”
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    A Novel Color Difference-Based Method for Palette Extraction and Evaluation Using Images of Birds by Melike Bektas Kosesoy, Seckin Yilmaz

    Published 2025-01-01
    “…In this study, a new color palette extraction and evaluation method is proposed that differs from existing methods because it accelerates designers’ product coloring processes by identifying the color-area and color-neighborhood relationship. …”
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    Crowdsourcing Evaluation of Video Summarization Algorithm by Avrajyoti Dutta, Dawid Juszka, Mikołaj Leszczuk

    Published 2024-11-01
    “…In this study, we offer a crowdsourcing subjective experiment in which summaries of processed video sequences are evaluated. Thus, we are proposing an experiment that utilizes crowdsourcing to evaluate the efficacy of an algorithm that summarizes videos. …”
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    Firefly algorithm with multiple learning ability based on gender difference by Wenning Zhang, Chongyang Jiao, Qinglei Zhou

    Published 2025-08-01
    “…To address these issues, a firefly algorithm with multiple learning ability based on gender difference (MLFA-GD) is proposed. …”
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    Evaluating Subpixel Target Detection Algorithms in Hyperspectral Imagery by Yuval Cohen, Yitzhak August, Dan G. Blumberg, Stanley R. Rotman

    Published 2012-01-01
    “…We demonstrate our ability to evaluate detectors and find the best settings for their free parameters by comparing our results using the following stochastic algorithms for target detection: the constrained energy minimization (CEM), generalized likelihood ratio test (GLRT), and adaptive coherence estimator (ACE) algorithms. …”
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    Opportunities and challenges of multidisciplinary algorithmic impact assessments by Juana Catalina Becerra Sandoval, Felicia Jing, Adriana Alvarado Garcia, Sara E. Berger, Heloisa Candello, Caitlin Lustig

    Published 2025-12-01
    “…However, the evaluation of computational and algorithmic systems has largely been approached through a uni-modal and uni-disciplinary perspective that heavily privileges computer science and engineering disciplines. …”
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    Decision-Making Support for the Evaluation of Clustering Algorithms Based on MCDM by Wenshuai Wu, Zeshui Xu, Gang Kou, Yong Shi

    Published 2020-01-01
    “…However, different algorithms can produce different or even conflicting evaluation performance, and this phenomenon has not been fully investigated. …”
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    Gray Extreme Weighted Sum Image Ringing Evaluation Algorithm by KE Ming, ZHANG Tian-ming, QIN Ai-jing, WANG Bo, BAI Xu

    Published 2019-10-01
    “…In the process of image blind restoration, the estimation of the fuzzy kernel usually produces errors which lead to image ringing The existing algorithm cannot effectively evaluate the severity of ringing To solve this problem, a method for evaluating the ringing effect is proposed From the physical mechanism of image ringing effect caused by blind restoration of image, the causes of the ringing effect caused by blind restoration of images and the influence on image quality are analyzed By extracting the overshoot and ripple regions of the ringing image and weighting the gradient values of the region, the severity of the ringing effect is quantified The experimental results show that when the fuzzy kernel parameter value exceeds 3, the algorithm shows a monotonically increasing state with increasing parameters,The change in SSIM evaluation results tends to be zero This algorithm can effectively evaluate different restoration algorithms and different restoration parameters Restore the ringing effect in the image under different restoration parameters…”
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