Real-time object classification using Apple's CoreML and Vision frameworks
Used Inceptionv3, an efficient Convolutional Neural Network Classifier for object recognition. Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, person etc. The top-5 error from the original publication is 5.6%.