Research Highlight

3D Segmentation and Classification using Learning Methods

Classification, Segmentation, and Geometric Analysis of 3D Point Clouds using Deep Learning

A new generic approach for over-segmentation in 3D point cloud data in general and specifically adjusted for bone porous micro-structures and their unique properties. Read more…

Fractographic Image Analysis Using Computer Vision and Deep Learning Methods

Computerizing one of the most challenging and time-consuming stages of the fractographic analysis process: locating fatigue striations on SEM (Scanning Electron Microscope) images. Read more…

3D Point Cloud Registration for Localization Using a Deep Neural Network Auto-Encoder

A novel methods for registration between a large-scale point cloud and a close-proximity scanned point cloud, providing a localization solution that is fully independent of prior information. Read more…
Bio analysis using Learning Methods

Computational diagnosis of Diabetic Macular Edema using deep learning techniques on Optical Coherence Tomography data

Promoting the clinical care of DME, by computational-based quantitative and qualitative analysis of OCT. Applying novel deep-learning methods on OCT data, including volumetric and longitudinal data. Read more…

Microstructure design and analysis of bio-degradable bone scaffolds

Optimal design of bio-degradable bone scaffolds taking into consideration the scaffolds’ mechanical strength over time as it degrades while living bone cells grow upon it. This geometrical change of shape along with the non-trivial structure makes calculation of structural integrity an intricate task. Read more…

Personalized Medicine: 3D Hierarchical Geometric Modeling and Multiscale Mechanical Analysis for Bone tissue

Closing the gap between the classic homogenization approach that is applied to macro-scale models and the modern micro-finite element method that is applied directly to micro-scale high-resolution models. Read more…
Robotics | Man-Machine Interface | Motion Detection

Human Motion Prediction using Learning Method for Human-Robot Collaboration In Assembly Tasks

What if the robot could observe human motions analyze them, and predict their motions and intentions? This will enable robot to work in close proximity with humans and opens new possibilities for customized and flexible Assembly and manufacturing processes. Read more…

Dimension Extraction from 3D Scanned Hand Model for Prosthesis Design using Deep-Learning Methods

A new method for dimensions extraction from three-dimensional scans that allows the creation of personalized hand-prosthesis without additional engineering design, using a DNN for dimension extraction and adjusting relevant dimensions to a 3D CAD model. Read more…


Reconstruction of a 3D model from a scanned scene using deep learning method

Predicting 3D model geometric parameters from a scanned scene by utilizing Deep-Learning techniques  that directly consumes point clouds. We propose to compare two different architectures for the prediction. The first network predicts the desired parameters directly in a supervised manner. The second network consists in an autoencoder that learns the features of the 3D model in an unsupervised manner. Read more…
3D Parametric Modeling using Learning Methods

Geometric parameters extraction for 3D model reconstruction from a scanned scene using Deep Learning methods

Extraction of geometric dimensions from a 3D point cloud of a scanned object using 3D reconstruction techniques and deep learning methods

Automatic Calculation of Physical Dimensions of Objects from a RGBD Image Using Deep Learning Methods