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

SIPL students win ECCV 2022 best demo award

SIPL students won ECCV 2022 best demo award ‘for demonstrating interesting applications that can enhance... Read More

SIPL students present a demo at ECCV 2022

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

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.

Seeing Sound: Estimating Image From Sound

The goal of this work is to train a deep neural network so that it can receive an audio signal as input and output a reconstructed image of the source from which that audio signal was produced. …
Stress Recognition using Physiological Data

In this work, we dealt with a physiological signal called EDA, the Electrical Dermal Activity of the skin. Under the assumption that changes in an individual’s mental and emotional state produce …
Finding Safe Landing Zones For VTOL Aircraft Using a LiDAR Sensor And Camera

In cases of natural disasters or during war, many casualties are expected in urban areas, many roads may be blocked and the access to wounded on roads will be almost impossible. The initial …
Digitizing Hand-drawn Circuit Diagrams

This work is an application that converts a drawing of an electrical circuit to a digital simulation tool.
The circuit can be drawn on different backgrounds: pen on paper, on a whiteboard, …
Quantification of penetration of Cancer on a Gel surface

The main goal of this work is to develop an algorithm which classifies depth of indentation for each shown cell in a given surface image. In the first step, we developed an algorithm that …
A PROOF OF CONCEPT AND PERFORMANCE EVALUATION OF 𝑩^𝟐 𝑹^𝟐 ALGORITHM FOR MODULO SAMPLING

When sampling an audio signal and converting it to a digital, discrete signal, we face several challenges that put the samples at risk of loss of information. One of those risks is driven by the …
Prediction of Anesthesia Depth based on EEG Signals

Spinal Surgery is a high-risk procedure with sever potential complications including paralysis and permanent sensory loss. Most of these complications are preventable or can be mitigate using …
Compressed IF-TEM: Time Encoding Analog-to-Digital Compression

An integrate-and-fire time-encoding-machine (IF-TEM) is an energy efficient asynchronous sampler. Utilizing the IF-TEM sampler for bandlimited signals, we introduce designs for time encoding and …

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