The thesis deals with the problem of multiview object recognition with a mobile application. To achieve this, we have used the neural network architecture called Inception, that uses the Tensorflow environment which enables simple modifications of the learning process. We used a specific collection of images, to help us objectively and realistically evaluate how well the object recognition works. We have presented good practices and we have applied that knowledge in the development of our object recognition. We have also examined various effects of different parameters such as number of iterations and training samples. We have combined it all and modified the model for recognising our own selected categories and maximising the results of the object recognition. Using Android Studio we have transferred the generated model to a mobile device.
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