Microcontroller Machine Learning

Classifying Clothing Items using Artificial Neural Networks on Cainvas Platform

Photo by Ofspace Digital Agency on Dribbble Introduction Neural Network is a programming paradigm inspired from the biological neurons in the human body. The neural networks are a set of algorithms that are modeled after the human brain, that are designed to capture patterns from the observational data. Today neural networks are used in a plethora …

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Signature Forgery Detection using Deep Learning

Photo by ForSureLetters on Dribbble In this age of digitalization, everything is online, paying bills, placing orders, filling documents, songs, etc. As more and more activities comes to online platforms a really important problem arises how to check the authority of the person on the Net. Of course Passwords can’t be used every time and especially …

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Encroachment Detection System based on anomalies in Network — Using Deep Learning

Photo by Evgenia Eiter on Dribbble Network encroachment detection systems (NEDS) are installed at a predetermined point in the network to analyze traffic from all connected devices. It monitors all subnet traffic and compares it to a database of known threats. An alarm can be issued to the administrator whenever an assault has been detected or …

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Gesture recognition using muscle activity — on cAInvas

Mapping muscle activity data to the gestures that they result in. Photo by Yohanen on Dribbble Electromyography is a technique for recording and evaluating electrical activity produced in the skeletal muscles. The readings from the muscle activity sensor are then fed to a model that can be trained on gestures, separately for each user (customization for …

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Handwritten Optical Character Recognition Calculator using CNN and Deep Learning

Photo by Pavelas Laptevas for Cub Studio on Dribbble Handwritten Character Recognition is often considered as the “Hello World” of Modern Day Deep Learning. Handwritten Optical Character Recognition has been studied by researchers and Deep Learning practitioners for decades now. It is by far the most understood area in Deep Learning and pattern recognition. Anyone starting …

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