Home Page - VISL

Autonomous Outdoor Garbage Cleaning System

Students in VISL develop the Garbage Cleaning System which addresses garbage left by travellers. The... Read More

Autonomous Outdoor Drones Activity

Autonomous Drones Demo at TCE2019 Conference

VISL Students in Unmanned Aerial Systems Contest

Lab Open Days

Twice a year the VISL takes part in the Open Lab Event, where students are... Read More

The Vision and Image Sciences Laboratory (VISL) was established in 1975 and since then is active in research and teaching in a wide range of topics related to Biological and Computer Vision Systems and Image and Video Processing. Particularly, in the last years, the lab is active in Image Enhancement Methods, Real-time Computer Vision Systems, Target Tracking, Aerial Image Processing, Underwater Imaging, 3D Imaging, Geometrical Approaches in Image Processing, Medical Imaging, and many more.

A dozen of graduate students work currently on their research in the VISL. About 50 undergraduate students complete their final BSc project and about 200 students take part in lab experiment courses in the VISL each year.

The VISL provides its students an opportunity to gain experience through projects and research. In addition to its educational role, the research and projects carried out in the lab directly contribute to the Hi-tech industry and to other collaboration partners such as medical centers and government. The activity of the lab is often driven by the needs of the science-based industry. Certainly, the research and projects carried out in the lab keep in the forefront of the activity in its fields of interest.

Autonomous Multi Robot Collaborative Exploration (Mapping)

LSD-SLAM and ORB-SLAM was implemented on a Turtlebot robot working under ROS for mapping and exploration purpuses.

Posted in: 3D and Depth, Applications, Autonomous Systems, Computer Vision
Image Based Smoke Detection

Create data set and train Resnet for smoke classification in images

Posted in: Computer Vision, Neural Neworks
Marine Object Detection Using Deep Learning

Recognition and identification of obstacles around USV using YOLO network

Posted in: Autonomous Systems, Computer Vision, Neural Neworks
Change Detection in CT Scans

Registration and change detection of CT scans using geometrical methods in image processing

Posted in: Medical Imaging
Autonomous litter picking robot for cleaning nature

This project is a first stage in development of an autonomic robot for picking up litter left in nature.

Posted in: Autonomous Systems, SYSTEMS
Structured Light In Scattering Media

This project presents structured light method for calculating object surface using projected light stripes

Posted in: 3D and Depth, Computer Vision
Flying Drones Video Dataset Augmentation

Build video dataset of flying drones for drone detection network

Posted in: Autonomous Systems, Computer Vision, Drones, Neural Neworks
Smart Street Lights

IoT System to be in stalled on Smart Street Lights based on Raspberry Pi and Amazon web service.

Posted in: Applications, Computer Vision, ITS
Automatic Tumor Classification in Mammogram Images

Use morphological features for classification of benign or malignant tumors in mammogram images

Posted in: Computer Vision, Medical Imaging
Traffic Regulation in HaBima Parking Lot

Monitor traffic conditions under hard conditions at the exit of Tel Aviv HaBima parking lot

Posted in: Computer Vision, ITS
Depth Enhancement Using RGB-D Fusion

Improve the STGV algorithm for depth recovery using state of the art Deep Learning based segmentation techniques

Posted in: 3D and Depth, Computer Vision, Neural Neworks
Turbulence Simulator

Atmospheric turbulence simulator using given parameters of user input

Posted in: Applications, Image Enhancement
Estimating Boat Tilt Angle Using Horizon Line

We present an improved algorithm for horizon calculation for USV from video taking into account the boat's oscillations due to waves.

Posted in: Autonomous Systems, Computer Vision
Neural Network for Drone Detection in Urban Environment

Training a YOLOv4 network for drone detection and implementation on an NVIDIA Jetson TX2 installed on a UAV

Posted in: Autonomous Systems, Computer Vision, Neural Neworks
Autonomous Drone Navigation Using Ground Stereo Cameras

Control a single drone using a ground stereo camera system

Posted in: Autonomous Systems, Computer Vision, Drones, SYSTEMS
Automatic Drone Navigation from Ground Camera

Autonomous drone localization and navigation from ground station camera

Posted in: 3D and Depth, Autonomous Systems, Computer Vision, Drones, SYSTEMS
Coral Segmentation and Identification

Segmentation of corals using data augmentation and training of existing ConvNet

Posted in: Computer Vision, Neural Neworks
Estimation of Cardiovascular Fitness from Cardiac Manifested Respiratory Pattern

In this research we investigate new ways to estimate cardiovascular health using Respiratory Sinus Arrhythmia (RSA), which can be seen in Heart Rate Variability (HRV) signal.

Posted in: Applications, Digital Health, Medical Imaging
Tomography through Successive Orders of Scattering

New method of stochastic tomography that relies on separation to different orders of scattering

Posted in: 3D and Depth
Imaging Around Corners Using ToF

Analysis of a hidden scene by Time of Flight (ToF) using MITSUBA simulation tool

Posted in: 3D and Depth, Computer Vision
Improving Transfer Learning For Breast Cancer Detection

Building models to improve transfer learning techniques for breast cancer detection using small data sets of mammograms and US scans

Posted in: Computer Vision, Medical Imaging, Neural Neworks
Liver Texture Analysis using CT Scans

Characterize liver pathologies by texture analysis using Wasserstein's metric

Posted in: Medical Imaging
Autonomous Navigation of Formula Vehicle using Thermal Camera

Estimate vehicle's position with respect to cones by using a thermal camera

Posted in: 3D and Depth, Autonomous Systems, Computer Vision, ITS
Anti-spoofing in Face Recognition Systems

Anti-spoofing by using a dual camera system to capture image depth from two different angles

Posted in: 3D and Depth, Applications, Computer Vision, SYSTEMS

VISL - Contact: jo@technion.ac.il | Powered by