Fully Funded PhD Position in Image Reconstruction using FPGA-based Generative AI
Summary of PhD Program:
The project aims at building accelerators based on Field Programmable Gate Arrays (FPGAs) and suitable to deliver computer vision tasks through Generative AI. Generative Adversarial Networks (GANs) based on Convolutional Neural Networks (CNNs) are promising candidates in this direction: they exploit adversarial learning and feature extraction to execute a multitude of applications, including image dataset generation, image-to-image translation, face frontalisation. Specifically, the project targets deploying applications like this on FPGA-based Systems-on-Chip (SoCs) to be showcased in real-time systems, with an in-depth investigation on optimisation techniques to reach high throughput and low energy footprint (e.g., data quantisation and pruning).
Application Deadline: May 20, 2025
SOURCE: FELLOWSHIPBARD
