FPGA accelerated Image Classification using Neural Networks The aim of the project is to speed up Image Classification by neural networks using FPGA's. The program will classify an image into one of the classes of the dataset under consideration. The result would be the correct classification of a non-labelled image into one of the classes of the dataset under consideration with faster execution time when accelerated using FPGA. The implementation generated will provide low latency and high throughput as compared to using only software classifiers in Image classification applications.