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Blood Cell classification using Deep Learning on Cainvas Platform

 Photo by Dana Pavlichko for Happy Cog on Dribbble     Introduction Blood is a constantly circulating body fluid which delivers nutrients and oxygens to the cells and aids in the transport of metabolic by-products away from the cells. It is one of the most vital components of the human body and multiple functionalities of the …

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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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