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Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Neha Sharma,Amlan Chakrabarti,Alfred M. Bruckstein Conference proceedings 2

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Automated Text and Tabular Data Extraction from Scanned Document Imagesgnificantly sped up by automating the data extraction from the scanned documents. The automation will also significantly reduce the time and effort needed for the data extraction and can be a valuable opportunity for an organization to reduce costs. A solution is proposed which makes use of open-sou
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Literature Survey: Sign Language Recognition Using Gesture Recognition and Natural Language Processithat translates Indian Sign Language to the corresponding English language excerpt. For this, the visual, as well as non-visual input of Sign Language signs, have to be processed, translated into English words, and then these words have to be put together into a grammatically correct and meaningful
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Application of Deep Learning Techniques on Sign Language Recognition—A Surveyocus on effectively recognizing signs under computing power constraints. The work primarily includes recognizing sign languages using discrete cosine transforms, principal component analysis, and hidden Markov models. Researchers have used a wide variety of machine learning and deep learning techniq
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https://doi.org/10.1007/978-3-319-53753-5erence engine efficiently for correct diagnosis and prescription. One of the important steps during the verification, validation, and evaluation of MPS, is Rule Base refinement. In this paper, authors have tried to formulate the Rule Base (RB) Refinement Scheme for their proposed Medicinal Prescript
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Cognitive Theory and Documentary Filmthe most promising results in cancer prediction, survivability analysis, and helping doctors in making informed decisions on treatment. With the advancements in imaging techniques, Feature selection and Classification on these images using deep neural network is showing promising results in diagnosi
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