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  • Image feature extraction is an important analysis tool in many computer vision applications. In this work, we look at sparse depth estimation in stereo vi
    3 KB (487 words) - 14:57, 13 May 2015
  • ...emand for high-speed image processing and recognition. Traditional machine vision systems are composed of image sensors and general-purpose processor.In this ...learning algorithm steps directly ion hardware and interface with the host computer system.
    3 KB (357 words) - 17:53, 6 December 2014
  • : Introductory course in computer vision (optional) : Interest in computer graphics / computer vision
    3 KB (366 words) - 11:40, 1 June 2017
  • Image feature extraction is an important analysis tool in many computer vision applications. In the context of this project, it is specifically used for s : Introductory course in computer vision (recommended)
    3 KB (373 words) - 10:51, 19 August 2017
  • ...yperspectral-cameras-2015-brochure.pdf pdf], [http://www.ximea.com/en/usb3-vision-camera/hyperspectral-usb3-cameras link]]. These new cameras are only 31 gra * Interest in computer vision and system engineering
    6 KB (941 words) - 10:29, 5 February 2016
  • ...ess and its potential applications to sensor networks, robotics, low-power vision and other fields. An interesting approach is that followed by the IBM TrueN * to have basic prior knowedge of hardware design and computer architecture (i.e. have followed the relative courses)
    5 KB (784 words) - 13:50, 30 November 2016
  • ...of multiple layers of filter banks. Almost all state-of-the-art synthetic vision systems are based on features extracted using multi-layer convolutional net ...lo and Y. LeCun, "NeuFlow: A Runtime Reconfigurable Dataflow Processor for Vision", Proc. IEEE ECV'11@CVPR'11 [http://ieeexplore.ieee.org/xpls/icp.jsp?arnumb
    9 KB (1,289 words) - 18:45, 24 March 2015
  • ...n often achieve better efficiency and generality than traditional computer vision techniques. With that in mind, we want to explore their effectiveness on ba
    3 KB (480 words) - 18:08, 28 January 2017
  • ...r alone. In low power computing, they allow complex tasks such as computer vision or cryptography to be performed under a very tight power budget. Without a
    2 KB (275 words) - 16:05, 24 November 2023
  • Optical flow is an essential ingredient to many complex computer vision systems. There are already quite a few algorithms to determine the optical ...workstations. This puts real-time applications out of reach where computer vision is most interesting: on low-power and mobile platforms, in cars, ...
    5 KB (707 words) - 10:22, 5 February 2016
  • ...of multiple layers of filter banks. Almost all state-of-the-art synthetic vision systems are based on features extracted using multi-layer convolutional net * Interest in computer vision, signal processing and VLSI design
    8 KB (1,145 words) - 10:30, 5 February 2016
  • ...of multiple layers of filter banks. Almost all state-of-the-art synthetic vision systems are based on features extracted using multi-layer convolutional net * Interest in VLSI and sustem design, and computer vision
    8 KB (1,197 words) - 17:18, 29 August 2016
  • : Introductory course in computer vision (optional) : Interest in computer graphics / computer vision
    2 KB (302 words) - 09:29, 5 November 2019
  • : Introductory course in computer vision (optional) : Interest in computer graphics / computer vision
    3 KB (373 words) - 18:40, 14 April 2016
  • ...adding communication capabilities to transmit suspicious cases to a remote computer and/or to add additional sensors (GPS, microphone). We would also like to p * Some experience programming (Computer Science 1+2 or equivalent)
    8 KB (1,176 words) - 15:26, 30 October 2020
  • ...of multiple layers of filter banks. Almost all state-of-the-art synthetic vision systems are based on features extracted using multi-layer convolutional net : Motivation for FPGA design and computer vision.
    3 KB (397 words) - 17:17, 29 August 2016
  • ...wn break-through performance and/or performance-per-power on many computer vision tasks such as classification, image segmentation, optical flow and super-re
    2 KB (285 words) - 17:16, 29 August 2016
  • ...on Ultra Low Power (ULP) accelerators we are developing the first Computer Vision (CV) library in such domain. In this project, you will port a set of existing vision algorithms, based on the VlFeat library [1], on the PULP platform, dealing
    4 KB (628 words) - 15:16, 20 February 2018
  • ...of multiple layers of filter banks. Almost all state-of-the-art synthetic vision systems are based on features extracted using multi-layer convolutional net * Interest in computer vision and system engineering
    5 KB (747 words) - 17:04, 29 August 2016
  • ...of multiple layers of filter banks. Almost all state-of-the-art synthetic vision systems are based on features extracted using multi-layer convolutional net * Interest in VLSI architecture exploration and computer vision
    9 KB (1,263 words) - 17:52, 12 December 2016

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