BEFinalProject

• A fruit detection and quality analysis using Convolutional Neural Networks and Image Processing.
• Dataset sources: Imagenet and Kaggle.
• Applied GrabCut Algorithm for background subtraction.
• Applied various transformations to increase the dataset such as scaling, shearing, linear transformations etc.
• Trained the models using Keras and Tensorflow.
• Training accuracy: 94.11% and testing accuracy: 96.4%