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Titlebook: Applied Computer Vision and Image Processing; Proceedings of ICCET Brijesh Iyer,A. M. Rajurkar,Venkat Gudivada Conference proceedings 2020

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https://doi.org/10.1007/978-1-349-02417-9e model the summarizer using deep learning algorithms using bi-RNNs and attention mechanisms. Furthermore, a hardware model is made to turn and capture images of pages from a book automatically using raspberry pi.
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E. M. Wilson PhD MSc FICE FASCED information from the feed to detect road lanes and to detect objects for analysing the distance of it from the vehicle to prevent collisions. Collision detection and prevention is based on the object detection and recognition using ML model which is capable of detecting any objects, like vehicle, pedestrians, animals and so on.
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https://doi.org/10.1007/978-0-387-09736-7ent records fused with the first six PCA dimensions. Similar detection accuracy was achieved using the first six LDA dimensions. Relative detection accuracy of fused features increased by 15 and 3% compared to detection accuracy with the original patient record and PCA features without fusion, respectively.
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Designing the Identities of Engineerssed to make noisy frames which helps in preserving the typical texture of speckle noise generated in real medical ultrasound images. The sets of data include real ultrasound images displayed from in vivo raw RF ultrasound echo.
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2194-5357 Focusing on applied computer vision and image processing, this proceedings volume includes papers on image processing, computer vision, pattern recognition, and DSP/DIP applications in healthcare systems. .978-981-15-4028-8978-981-15-4029-5Series ISSN 2194-5357 Series E-ISSN 2194-5365
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E. M. Wilson PhD MSc FICE FASCE and contrast stretching method which permits better visual appearance of an image. Also here we have proposed design for finding region of interest in an image by developing eight different grey levels which can be used in detecting object in an image as it is one of the major areas of research in biometric application.
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