Titlebook: Computer Vision and Image Processing; 4th International Co Neeta Nain,Santosh Kumar Vipparthi,Balasubramanian Conference proceedings 2020 S

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书目名称Computer Vision and Image Processing影响因子(影响力)




书目名称Computer Vision and Image Processing影响因子(影响力)学科排名




书目名称Computer Vision and Image Processing网络公开度




书目名称Computer Vision and Image Processing网络公开度学科排名




书目名称Computer Vision and Image Processing被引频次




书目名称Computer Vision and Image Processing被引频次学科排名




书目名称Computer Vision and Image Processing年度引用




书目名称Computer Vision and Image Processing年度引用学科排名




书目名称Computer Vision and Image Processing读者反馈




书目名称Computer Vision and Image Processing读者反馈学科排名

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https://doi.org/10.1007/978-1-4302-2642-0mation from them. A key step used in image processing involves the removal of different kinds of noises from the images. Noises can arise in an image during the process of storing, transmitting or acquiring the images. A model qualifies as a satisfactory de-noising model if it satisfies image preser

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https://doi.org/10.1007/978-1-4302-2642-0alyzing and studying handwriting is .. The prime features of handwriting such as margins, slanted, the baseline can tell the characteristics of a writer. The writer handwriting analysis reveals strokes and patterns through which identification and understanding the personality of a writer is possibl

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Restrict Physical Access to Cardholder Data,llular characteristics of the cells of a suspicious breast tumor. A computer-aided automatic classifier with the help of machine learning can improve the diagnosis system in terms of accuracy and time consumption. These types of system can automatically distinguish a benign and malignant pattern in

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The Definitive Guide to PCI DSS Version 4sponding to the legitimate user. Thus, it is essential to develop a Presentation Attack Detection (PAD) algorithms that can automatically detect the presentation attacks the face recognition systems. In this paper, we present a novel method for face presentation attack detection based on the multi-c

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https://doi.org/10.1007/978-1-4302-1894-4y driver being sleepy. A drowsiness detection solution should be very accurate and run in real-time. All the existing deep learning solutions for drowsiness detection are computationally intensive and cannot be easily implemented on embedded devices. In this paper, we propose a real-time driver drow

Resistance

Managing Security and Workflowsy diet. If we can predict a stroke in its early stage, then it can be prevented. In this paper, we evaluate five different machine learning techniques to predict stroke on Cardiovascular Health Study (CHS) dataset. We use Decision Tree (DT) with the C4.5 algorithm for feature selection, Principal Co