16 May, 2022

Embedded Vision Summit 2022

Join Imagination and hundreds of computer vision professionals at the Embedded Vision Summit

We will be at Booth 412 in the Santa Clara Convention Center from May 16–19, come visit our team there and watch our latest demos in action. We are delighted to offer you a discount on registration – use Promo Code SUMMIT22-PARTNER when you register.

This annual event brings together a global audience of companies developing leading-edge, vision-enabled products, including embedded systems, cloud solutions, and mobile applications.

Technical Insight Presentation 

Don’t miss the opportunity to listen to one of our experts present our research into novel techniques for representing signal processing operations as neural networks and how to execute them as part of a neural network.

Title: Representing Fourier Transforms and Advanced Signal Processing as Convolutional Neural Networks

Speaker: Cagatay Dikici, Senior Research Manager, Imagination Technologies

Time: Tuesday, May 17 – 11:25 am PT


We present novel techniques for representing signal processing operations such as frequency-domain transforms, spectrogram generation, and MFCC extraction as neural networks. In many applications, signal processing operations are performed in a separate step before a neural network (i.e. data preprocessing) or as a layer inside the neural network itself. Examples of such applications include radar, audio, and medical imaging, all of which typically involve Fourier analysis. In such applications, it is often advantageous to represent signal processing operations in terms of common neural network layers, such as convolutions, elementwise and split/concatenate operations. By representing signal processing operations as neural networks, it is possible to execute them as part of a neural network.

Speaker Bio

Cagatay Dikici is a Senior Research Manager in the AI Research Team at Imagination Technologies in London. He received his PhD in Computer Science from INSA de Lyon, France. His research interests include machine learning, computer vision, and information theory in general. At Imagination, he works primarily on neural network accelerators and low-precision inference targeting embedded systems. He has 8 years of experience as a researcher in the semiconductor IP industry, during which time he has led and contributed to more than 30 publications and patents.