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Titlebook: Computational Intelligence and Big Data Analytics; Applications in Bioi Ch. Satyanarayana,Kunjam Nageswara Rao,Richard G. Book 2019 The Au

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41#
發(fā)表于 2025-3-28 17:06:59 | 只看該作者
42#
發(fā)表于 2025-3-28 20:30:31 | 只看該作者
https://doi.org/10.1007/978-3-319-63745-7enhancement, entropy to measure richness of the details of the image. The proposed results show that the Adaptive Histogram Equalization is the best enhancement method which helps in the detection of diabetic retinopathy in fundus images.
43#
發(fā)表于 2025-3-29 02:55:33 | 只看該作者
Introduction: The Strength of Stories,he various data mining techniques can accelerate this computation task and help in accurate and fast toxicity prediction. This paper leads the readers to work in this area, by providing a groundwork of the data, tools, and techniques used, along with future research directions.
44#
發(fā)表于 2025-3-29 05:57:41 | 只看該作者
https://doi.org/10.1007/978-3-030-19266-2ing (soft and hard thresholding)-based noise reduction algorithm is employed. Finally, the calculation of different performance measures enables us to choose an efficient technique. The accuracy and consistency of the proposed method are shown in experimental results.
45#
發(fā)表于 2025-3-29 11:00:51 | 只看該作者
46#
發(fā)表于 2025-3-29 12:56:59 | 只看該作者
A Quantitative Analysis of Histogram Equalization-Based Methods on Fundus Images for Diabetic Retinenhancement, entropy to measure richness of the details of the image. The proposed results show that the Adaptive Histogram Equalization is the best enhancement method which helps in the detection of diabetic retinopathy in fundus images.
47#
發(fā)表于 2025-3-29 17:12:13 | 只看該作者
Nanoinformatics: Predicting Toxicity Using Computational Modeling,he various data mining techniques can accelerate this computation task and help in accurate and fast toxicity prediction. This paper leads the readers to work in this area, by providing a groundwork of the data, tools, and techniques used, along with future research directions.
48#
發(fā)表于 2025-3-29 20:24:39 | 只看該作者
Performance Analysis of Denoising of ECG Signals in Time and Frequency Domain,ing (soft and hard thresholding)-based noise reduction algorithm is employed. Finally, the calculation of different performance measures enables us to choose an efficient technique. The accuracy and consistency of the proposed method are shown in experimental results.
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