PatternRecognition_Matlab:Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).
Yoga-Pose-Estimation-App:This is a Yoga Pose Estimation App which can be able to detect the yoga pose in real time by using posenet and KNN Classifier. Here the dataset used is custom data set which consists of 3 videos for representing 3 different postures. It is deployed in heroku. One Thing to be noted i.e this will work correctly for all mobile and edge devices.
Sign-Language-Translator:Sign Language Translator enables the hearing impaired user to communicate efficiently in sign language, and the application will translate the same into text/speech. The user has to train the model, by recording its own sign language gestures. Internally it uses MobileNet and KNN classifier to classify the gestures.
// repository documentation
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