NVIDIA Jetson for Embedded, How high-performance and low-energy computing systems for deep learning and computer vision can help Robotics

نویسنده

  • Serge Palaric
چکیده

Serge Palaric joined NVIDIA in 2004 after 20 years working at different OEMs as Dell, Packard Bell and NEC on mobile devices at European level. Focused on system design wins at key global accounts; He is in charge of embedded business at NVIDIA covering Europe with a focus on IVA and Autonomous machines where Computer Vision and Deep Learning are key leading technologies.

منابع مشابه

Real-Time Robot Localization, Vision, and Speech Recognition on Nvidia Jetson TX1

Robotics systems are complex, often consisted of basic services including SLAM for localization and mapping, Convolution Neural Networks for scene understanding, and Speech Recognition for user interaction, etc. Meanwhile, robots are mobile and usually have tight energy constraints, integrating these services onto an embedded platform with around 10 W of power consumption is critical to the pro...

متن کامل

Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video

Object detection is considered one of the most challenging problems in this field of computer vision, as it involves the combination of object classification and object localization within a scene. Recently, deep neural networks (DNNs) have been demonstrated to achieve superior object detection performance compared to other approaches, with YOLOv2 (an improved You Only Look Oncemodel) being one...

متن کامل

A Novel Approach to Background Subtraction Using Visual Saliency Map

Generally human vision system searches for salient regions and movements in video scenes to lessen the search space and effort. Using visual saliency map for modelling gives important information for understanding in many applications. In this paper we present a simple method with low computation load using visual saliency map for background subtraction in video stream. The proposed technique i...

متن کامل

Embedded Real-Time Fall Detection Using Deep Learning For Elderly Care

This paper proposes a real-time embedded fall detection system using a DVS(Dynamic Vision Sensor)(Berner et al. [2014]) that has never been used for traditional fall detection, a dataset for fall detection using that, and a DVSTN(DVS-Temporal Network). The first contribution is building a DVS Falls Dataset, which made our network to recognize a much greater variety of falls than the existing da...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

متن کامل
عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015