Recognition of Handwritten Digits/Char using Machine Learning
Keywords:Machine Learning, Image processing, YOLO, Classification, TensorFlow, Nodejs, Pose estimation
Handwritten Digits/Characters an idea of recognize digit which is used for the computers. Object detection technique is used for detecting the digits and characters in English language i.e., digits from 0-9 and characters from (A-Z), (a-z) Capital letters and small letters. Object detection is performed by Cascade classifier. Cascade classifier class to detect objects in a video stream. The cascades are a bunch of XML files that contain OpenCV data used to detect objects. There are a unit 2 rule area unit employed in this technology i.e., create rule and YOLO rule. Pose estimation refers to laptop vision techniques that discover human figures in pictures and videos. The rule is just estimating wherever key body joints area unit. Human create estimation is the method of estimating the configuration of the body (pose) from one, usually monocular, image. YOLO is associate abbreviation for the term ‘You solely Look Once’. this is often associate rule that detects and acknowledges numerous objects in a very image (in real-time). Object detection in YOLO is completed as a regression downside and provides the category possibilities of the detected pictures. YOLO is an associate rule that uses neural networks to supply time period object detection. This rule is widespread attributable to its speed and accuracy. It has been employed in numerous applications to discover traffic signals, people, parking meters, and animals.
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Copyright (c) 2022 Kumbhar Rutuja Chandrakant, Gaikwad Shraddha Dhanaji, Kenjale Sanjana Ashok, Kadam Ujwal Namdeo
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