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• FPGA System Design for Computer Vision with Convolutional Neural Networks
  ...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) - 18:17, 29 August 2016

Page text matches

• Feature Extraction with Binarized Descriptors: ASIC Implementation and FPGA Environment
  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) - 15:57, 13 May 2015
• Image Sensor Interface and Pre-processing
  ...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) - 18:53, 6 December 2014
• Accelerator for Spatio-Temporal Video Filtering
  : Introductory course in computer vision (optional) : Interest in computer graphics / computer vision
  3 KB (366 words) - 12:40, 1 June 2017
• Accelerator for Boosted Binary Features
  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) - 11:51, 19 August 2017
• Improving Scene Labeling with Hyperspectral Data
  ...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) - 11:29, 5 February 2016
• Design and Implementation of Digital Spiking Neurons for Ultra-Low-Power In-Cluster Coprocessors
  ...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) - 14:50, 30 November 2016
• Design and Implementation of a Convolutional Neural Network Accelerator ASIC
  ...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) - 19:45, 24 March 2015
• Gomeza old project4
  ...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) - 19:08, 28 January 2017
• Acceleration and Transprecision
  ...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) - 17:05, 24 November 2023
• Real-Time Optical Flow Using Neural Networks
  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) - 11:22, 5 February 2016
• FFT-based Convolutional Network Accelerator
  ...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) - 11:30, 5 February 2016
• High-speed Scene Labeling on FPGA
  ...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) - 18:18, 29 August 2016
• Image and Video Processing
  : Introductory course in computer vision (optional) : Interest in computer graphics / computer vision
  2 KB (302 words) - 10:29, 5 November 2019
• Spatio-Temporal Video Filtering
  : Introductory course in computer vision (optional) : Interest in computer graphics / computer vision
  3 KB (373 words) - 19:40, 14 April 2016
• Improving our Smart Camera System
  ...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) - 16:26, 30 October 2020
• FPGA System Design for Computer Vision with Convolutional Neural Networks
  ...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) - 18:17, 29 August 2016
• Learning Image Decompression with Convolutional Networks
  ...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) - 18:16, 29 August 2016
• Covariant Feature Detector on Parallel Ultra Low Power Architecture
  ...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) - 16:16, 20 February 2018
• Change-based Evaluation of Convolutional Neural Networks
  ...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) - 18:04, 29 August 2016
• Rethinking our Convolutional Network Accelerator Architecture
  ...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) - 18:52, 12 December 2016
• FPGA acceleration of ultrasound computed tomography for in vivo tumor screening
  ...eases the speed of sound (SoS) and acoustic attenuation (AA). The computer vision laboratory at ETHZ developed and patented a hand-held ultrasound technology ...a [mailto:sasergio@vision.ee.ethz.ch sasergio@vision.ee.ethz.ch] (Computer Vision Lab ETHZ)
  3 KB (411 words) - 14:07, 30 August 2017
• Learning Image Compression with Convolutional Networks
  ...wn break-through performance and/or performance-per-power on many computer vision tasks such as classification, image segmentation, optical flow and super-re
  3 KB (362 words) - 16:25, 30 October 2020
• Bringing XNOR-nets (ConvNets) to Silicon
  ...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
  10 KB (1,357 words) - 16:25, 30 October 2020
• Real-time eye movement analysis on a tablet computer
  ...developing such a mobile eye tracker which can be controlled with a table computer running a custom, android-based app from the IIS.
  2 KB (319 words) - 15:09, 6 January 2022
• Sensor Fusion for Rockfall Sensor Node
  * Computer vision course (optional)
  2 KB (352 words) - 11:51, 21 August 2018
• Single-Bit-Synapse Spiking Neural System-on-Chip
  ...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 prior knowedge of hardware design and computer architecture - having followed the Advances System-on-Chip Design course is
  7 KB (1,000 words) - 12:22, 13 January 2017
• Convolution Neural Networks on our Ultra-Low Power Mult-Core Plattform PULP
  ...ing binary convolutional neural networks." European Conference on Computer Vision. Springer International Publishing, 2016. ...network accelerator based on binary weights." In VLSI (ISVLSI), 2016 IEEE Computer Society Annual Symposium on, pp. 236-241. IEEE, 2016.
  6 KB (823 words) - 08:36, 20 January 2021
• Variable Bit Precision Logic for Deep Learning and Artificial Intelligence
  ...performances in many fields, redefining the state of the art for computer vision, text and speech recognition, problem solving. * to have prior knowedge of hardware design and computer architecture - having followed the Advances System-on-Chip Design course is
  7 KB (1,001 words) - 10:43, 26 June 2017
• A Waypoint-based Navigation System for Nano-Size UAVs in GPS-denied Environments
  * Basic knowledge of Computer Vision (e.g., Visual Odometry).
  4 KB (605 words) - 16:35, 20 February 2018
• Human Intranet
  ...he functions provided by the body itself. Human Intranet presents a system vision in which, for example, disease would be treated by chronically measuring bi ...52/aab2f2/meta A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update]
  17 KB (2,419 words) - 20:09, 10 March 2024
• AMZ Driverless Competition Embedded Systems Projects
  ...the overhead of the network and to compute the first steps on the computer vision detection algorithms. ...g HW accelerators for part of the object detection algorithms for computer vision and/or LiDAR.
  6 KB (895 words) - 16:27, 30 October 2020
• Hardware Acceleration
  ...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
  7 KB (917 words) - 17:04, 24 November 2023
• BirdGuard
  This project aims to develop a solar-​powered and computer vision-​based sticker that can be mounted at the outside of a window to visually ...rning-based detection algorithms have revolutionized the field of computer vision and will thus be adopted for this application. The algorithm shall be valid
  5 KB (647 words) - 08:32, 23 February 2023
• A Flexible Peripheral System for High-Performance Systems on Chip (M)
  [[Category:Computer Architecture]] At IIS, we often tape out Systems on Chip (SoCs) to try out new computer-architectural concepts and extensions, often differentiated by small-scale
  11 KB (1,675 words) - 15:40, 15 March 2021
• A Snitch-based Compute Accelerator for HERO (M/1-2S)
  [[Category:Computer Architecture]] ...efficiency for embedded applications with heavier workloads, like computer vision tasks for unmanned aerial vehicles (UAVs) and machine learning inference.
  11 KB (1,617 words) - 23:59, 6 February 2021
• MemPool on HERO (1S)
  * to have prior knowledge of hardware design and computer architecture ...-low power parallel accelerator for energy-efficient and flexible embedded vision,”J. Signal Process. Syst., vol. 84, no. 3, p. 339–354, Sep. 2016.
  6 KB (902 words) - 19:07, 20 January 2021
• Combining Multi Sensor Imaging and Machine Learning for Robust Far-Field Vision
  Today, Machine Learning and Computer Vision are taking a central place in surveillance tasks. The surveillance of air s
  2 KB (349 words) - 15:53, 11 October 2021
• Low Resolution Neural Networks
  ...rious artificial intelligence tasks, including but not limited to computer vision and natural language processing. Due to high computational complexity, NNs [[Category:Computer Architecture]]
  4 KB (520 words) - 14:52, 24 November 2021
• Bridging QuantLab with LPDNN
  * Familiarity with computer vision tasks [[Category:Computer Architecture]]
  7 KB (831 words) - 19:36, 12 January 2023
• Efficient Execution of Transformers in RISC-V Vector Machines with Custom HW acceleration (M)
  [[Category:Computer Architecture]] ...uage processing and other recurrent machine learning tasks (e.g., computer vision, molecular dynamics).
  4 KB (549 words) - 11:35, 3 November 2023
• Enabling Efficient Systolic Execution on MemPool (M)
  [[Category:Computer Architecture]] ...power envelope as quickly as possible. Computational photography, computer vision, augmented reality, and machine learning are only few of the possible appli
  3 KB (422 words) - 10:39, 2 November 2023
• Christoph Leitner
  * Machine Learning and Computer Vision
  928 bytes (111 words) - 01:54, 12 January 2023
• Design of a High-​performance Hybrid PTZ for Multimodal Vision Systems
  <!-- High-performance Multimodal Computer-Vision Systems --> ...on-systed.png|450px|thumb|right|The envisioned high-performance multimodal vision system]]
  4 KB (572 words) - 11:07, 5 December 2023
• Pretraining Foundational Models for EEG Signal Analysis Using Open Source Large Scale Datasets
  ...ered the landscape in fields like natural language processing and computer vision. Nevertheless, their application in interpreting the complexities inherent * Yawei Li: yawei.li@vision.ee.ethz.ch
  7 KB (891 words) - 17:04, 18 December 2023
• Transformer Deployment on Heterogeneous Many-Core Systems
  ...l neural networks (CNNs) in natural language processing (NLP) and computer vision tasks. The self-attention mechanism is a key component of the model but res
  6 KB (858 words) - 14:52, 23 October 2023
• System Emulation for AR and VR devices
  In eyeglass systems, vision is one of the important pipelines. The images generated from the multiple s * Strong interest in computer architecture.
  4 KB (577 words) - 18:28, 4 October 2023