The Signal and Image Processing Lab - Signal and Image Processing Lab.

SIPL Annual Event 2022

You can find all the details about the event and register here:... Read More

SIPL students present their work at ICC 2022

SIPL undergraduate students wrote a paper describing their solution for the IEEE Signal Processing Cup... Read More

SIPL students present their paper at WAVC 2022

SIPL undergraduate students wrote a paper describing their project and presented it at WAVC 2002.... Read More

SIPL students present their papers at COMCAS 2021

Three papers written by undergraduate students and their supervisor were accepted to the conference and... Read More

SIPL students present their projects at COMCAS 2021

SIPL students present their projects at IMVC 2021

Two undergraduate projects were presented at the conference: A demo: Eye and Head Tracking for... Read More

The Signal and Image processing Lab (SIPL) was established in 1975 in the Department of Electrical Engineering of the Technion. It has been active since in research and teaching in a wide range of signal processing topics. Particularly, in the development and implementation of algorithms for processing speech, audio, image, video, physiological signals, point clouds, and more, widely using machine learning, and particularly deep learning. Many dozens of graduate students have since completed their research in the lab. In addition, over 100 undergraduate senior year students perform experiments and projects in the lab each year – many of them in collaboration with industry. SIPL has been involved through the years in many aspects and applications of signal processing and has provided its graduates an opportunity to gain experience in the field – through projects and research. In addition to its educational role, the research and projects carried out in the lab have directly contributed to the flourishing hi-tech industry in Israel. The activity of the lab was often driven by the needs of the science-based industry and we believe that it had an impact beyond the local scene. Certainly, the research and projects carried out in the lab kept it in the forefront of the activity in the field.

Speech-to-Singing Conversion Using Deep Learning

The purpose of this work is to develop an algorithm for converting speech to singing using deep learning methods. The system can help memorize various short texts like phone numbers and lists, …
Hyperbolic Representation Learning for EEG Signals

Brain-Computer Interface (BCI) is a fast-growing field in electrical engineering with many different applications. Neural researchers found different kinds of hierarchies in the brain, and in …
Image Colorization for Thermal Mobile Camera Images

Thermal image colorization is a topic that is gaining momentum in the world of artificial intelligence. In recent years, with a significant improvement in the tools, and with the algorithmic …
Ultrasonic User Authentication With Smartphones

The goal of this work is to implement a solution to the smart user authentication, without user’s contact with the workstation. The solution includes two applications; the first one is an …
Topological Hyperbolic Representation For Classification of Hyperspectral Images

In this work, we demonstrate the use and application of learning hierarchical data by embedding it into hyperbolic space. By applying the latest approaches in the field of machine learning and …
Depth from a Monocular Image and Sparse Metric Points

Today there are two main approaches to produce depth from a single RGB image – absolute measuring or relative estimation.
Absolute depth measurement is a reliable method that achieves …
Textual Explorable Super Resolution

In this work, we developed an explorable Super-Resolution model, which generates a high-resolution image that is both consistent with the original low-resolution image and consistent with the …
A System for Real-Time Deep Speech Denoising

Recorded speech is often mixed with a variety of background noises, such as a leaf blower, washing machine, dog barking, baby crying, kitchen noises, etc. Background noise significantly degrades …

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