Abstract: The character and symbol recognition system comprises a detachable body having a photographic camera to capture real time image of one of sheet or poster comprising of printed and handwritten characters and symbols; an input unit to acquire the real time captured image; a pre-processing unit to detect a character and symbol region; a classification unit equipped with at least two channel neural network based on CNN and LSTM to separate the character and symbol region; a central processing unit to calculate weights for transitions to the candidates thereby generate one of a first character or first symbol string transition data based on a set of the candidates and the weights; and a control unit to detect one or both of the printed and handwritten characters and symbols thereby display the detected information on a display unit and play the detected information on a speaker to alert a rider.

Abstract: The present disclosure generally relates to a method for COVID-19 detection for spread prevention and medical assistance using machine learning comprises pre-processing a CT image set for removing noise using HU values; performing a region-based segmentation using a three-dimensional convolutional neural network model; classifying each segmented region by employing a classification model; and comparing classified segmented region with a dataset for detecting COVID-19 using a machine learning approach thereby generating an alert about the COVID-19 positive person.