Dr. Ilan kadar

Dr. Ilan kadar

Director of Deep Learning
Nexar

Bio:

Ilan Kadar is the Director of Deep Learning at Nexar. Ilan is responsible for leading the deep learning team and effort to leverage Nexar's large-scale datasets of real-world driving environments to automotive safety applications. Prior to Nexar, Ilan was leading the deep learning group at Cortica and was responsible for building the company's machine vision technology. Ilan received his BSc, MSc and PhD degrees in computer science from the Ben-Gurion University of the Negev, Israel, in 2006, 2008, and 2012 respectively (Summa Cum Laude). His research thesis focused on machine learning algorithms for scene recognition and image retrieval, while employing insights from behavioral and psychophysical experiments. His work was published in leading conferences and journals in the areas of machine vision and was awarded the best research project at IMVC in 2013, the Intel award for excellent Israeli PhD students in 2012, and the Friedman award for outstanding PhD students in 2012.

Title:

MUNET: Multi-Task Unified Network for On-Device Autonomous Driving

Abstract:

Much progress has been made in the last two years on efficient object detection networks (e.g., YOLO9000, SqueezeDet and MobileNet). In this talk, we will address the unique challenges of autonomous driving applications that go beyond the traditional object detection methods. First, we will introduce a unified network that jointly performs various autonomous driving tasks in real-time on mobile to protect drivers on the road. Then, we will address the challenges that emerge when training a single mobile network for multiple tasks such as object detection, object attributes recognition, classification, and tracking. Next, we will describe a scalable pipeline for continuous training of mobile networks through hard negative mining. Finally, we will go over some of our advanced driver assistance applications that aim to make driving safer worldwide.