Results 171 to 180 of about 2,410 (200)

Neuromorphic Vision Systems for Mobile Applications

IEEE Custom Integrated Circuits Conference 2006, 2006
Neuromorphic vision systems are ideal for mobile applications because they promise compact computational sensing at lower power consumption compared to the traditional imager/ADC/CPU systems. These properties are particularly important for unmanned aerial vehicles.
Ralph Etienne-Cummings, Swati Mehta, Ralf M. Philipp, Viktor Gruev   +3 more
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Modeling of Neuromorphic Vision Sensors in ODE

Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2006
Three different neuromorphic vision sensors; a 2D smooth optical flow sensor, a 1D tracker sensor and a 1D motion sensor are modeled in a simulator. The sensors are modeled according to their spatio-temporal properties and the model is validated with experimental data obtained in previous work.
Vlatko Becanovic, Tobias Günther, Ansgar Bredenfeld   +2 more
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Accelerating neuromorphic vision algorithms for recognition

Proceedings of the 49th Annual Design Automation Conference, 2012
Video analytics introduce new levels of intelligence to automated scene understanding. Neuromorphic algorithms, such as HMAX, are proposed as robust and accurate algorithms that mimic the processing in the visual cortex of the brain. HMAX, for instance, is a versatile algorithm that can be repurposed to target several visual recognition applications ...
Ahmed Al-Maashri, Michael DeBole, Matthew Cotter, Nandhini Chandramoorthy, Yang Xiao 0002, Vijaykrishnan Narayanan, Chaitali Chakrabarti   +6 more
openaire   +1 more source

A framework for accelerating neuromorphic-vision algorithms on FPGAs

2011 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2011
Implementations of neuromorphic algorithms are traditionally implemented on platforms which consume significant power, falling short of their biologically underpinnings. Recent improvements in FPGA technology have led to FPGAs becoming a platform in which these rapidly evolving algorithms can be implemented. Unfortunately, implementing designs on FPGAs
Michael DeBole, Ahmed Al-Maashri, Matthew Cotter, Chi-Li Yu, Chaitali Chakrabarti, Vijaykrishnan Narayanan   +5 more
openaire   +1 more source

A hardware architecture for accelerating neuromorphic vision algorithms

2011 IEEE Workshop on Signal Processing Systems (SiPS), 2011
Neuromorphic vision algorithms are biologically inspired algorithms that follow the processing that takes place in the visual cortex. These algorithms have proved to match classical computer vision algorithms in classification performance and even outperformed them in some instances.
Ahmed Al-Maashri, Michael DeBole, Chi-Li Yu, Vijaykrishnan Narayanan, Chaitali Chakrabarti   +4 more
openaire   +1 more source

Neuromorphic Vision Hybrid RRAM-CMOS Architecture

IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2018
The development of a bioinspired image sensor, which can match the functionality of the vertebrate retina, has provided new opportunities for vision systems and processing through the realization of new architectures. Research in both retinal cellular systems and nanodriven memristive technology has made a challenging arena more accessible to emulate ...
Jason Kamran Eshraghian, Kyoungrok Cho, Ciyan Zheng, Minho Nam, Herbert Ho-Ching Iu, Wen Lei, Kamran Eshraghian   +6 more
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A New Robotics Platform for Neuromorphic Vision: Beobots

2002
This paper is a technical description of a new mobile robotics platform specifically designed for the implementation and testing of neuromorphic vision algorithms in unconstrained outdoors environments. The platform is being developed by a team of undergraduate students with graduate supervision and help.
Daesu Chung, Reid Hirata, T. Nathan Mundhenk, Jen Ng, Robert J. Peters, Eric Pichon, April Tsui, Tong Ventrice, Dirk B. Walther, Philip Williams, Laurent Itti   +10 more
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Invited paper: Accelerating neuromorphic vision on FPGAs

CVPR 2011 WORKSHOPS, 2011
Reconfigurable hardware such as FPGAs are being increasingly employed for application acceleration due to their high degree of parallelism, flexibility and power efficiency — factors which are key in the rapidly evolving field of embedded real-time vision. While recent advances in technology have increased the capacity of FPGAs, lack of standard models
Sungho Park, Srinidhi Kestur, Kevin M. Irick, Vijaykrishnan Narayanan   +3 more
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A neuromorphic saliency-map based active vision system

2011 45th Annual Conference on Information Sciences and Systems, 2011
Selective attention is a very efficient strategy for engineering active vision systems that need to extract relevant information from the scene in real-time. We propose an implementation of a saliency-map based active vision system in which Address-Event sensors and neuromorphic winner-take-all devices complement conventional imagers and machine vision
Daniel Sonnleithner, Giacomo Indiveri
openaire   +2 more sources

Neuromorphic vision sensors for computer vision

There have been significant advancements in the field of artificial intelligence (AI) over the past two decades, allowing such technologies to acquire popularity in both industry and academia. Face recognition software on Facebook or the iPhone, self-driving cars, and image recognition software are examples of AI applications that have become more ...
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