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Titlebook: Machine Learning, Image Processing, Network Security and Data Sciences; Second International Arup Bhattacharjee,Samir Kr. Borgohain,Xiao-Zh

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Handwritten Bengali Character Recognition Using Deep Convolution Neural Network,ave used 15,000 instances of Bengali alphabets to create a recognition model, which when provided with images of physical pieces of handwritten texts, it is able to segment and extract characters from the said image of a physical handwritten text with 65% accuracy, and recognize the properly segmented alphabets with 99.5% accuracy.
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Lexical Feature Based Feature Selection and Phishing URL Classification Using Machine Learning Technation of features with different numbers of features each time was evaluated to find the best possible combination of features. Performances are analyzed for different datasets with various parameters using four different machine learning techniques.
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Attention-Based English to Mizo Neural Machine Translation,tested for resource scare English to Mizo language pair. The quality of output translations have been evaluated using automatic evaluation metrics and analyzed the predicted translations based on best and worst performances of test data.
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Conference proceedings 2020, Network Security and Data Sciences, MIND 2020, held in Silchar, India. Due to the COVID-19 pandemic the conference has been postponed to July 2020. .The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions. The papers are organized according to the following
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Mining Composite Fuzzy Association Rules Among Nutrients in Food Recipe, of transactions. Fuzzy Association Rule Mining (FARM) emerged as a significant research area and is an extension of classical association rule mining which applies Fuzzy set theory to address the uncertainty in the case of categorical data. Different algorithms are proposed for Fuzzy Association Ru
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Legal Amount Recognition in Bank Cheques Using Capsule Networks, detection as a use-case in the computer vision ecosystem, it has been hampered by the deficiency of effective machine learning models to detect the language-specific legal amount on bank cheques. Currently, convolutional neural networks are the most widely used deep learning algorithms for image cl
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