The objective of this report is to implement a Convolutional Neural Network (CNN) in an FPGA, with a main focus on accelerating the training, using Maxeler technology as a way to compile higher level code directly into hardware.Neural Networks are one of the most commonly used models used in all sorts of tasks in Machine Learning. This type of network is mostly used for image recognition/generation, since a few layers ( convolutional, pooling) can be viewed as image operations to find features, which are then combined in the fully connected layer(s) and used to produce the output.
| Identifer | oai:union.ndltd.org:up.pt/oai:repositorio-aberto.up.pt:10216/122196 |
| Date | 17 September 2019 |
| Creators | Afonso de Sá Reis |
| Contributors | Faculdade de Engenharia |
| Source Sets | Universidade do Porto |
| Language | English |
| Detected Language | English |
| Type | Dissertação |
| Format | application/pdf |
| Rights | openAccess |
Page generated in 0.0053 seconds