System-on-chip for biologically inspired vision applications

IPSJ Transactions on System LSI Design Methodology

Volumn 5, Issue , 2012, Pages 71-95

  Park, Sungho ^a   Al Maashri, Ahmed ^a   Irick, Kevin M ^a   Chandrashekhar, Aarti ^a,b   Cotter, Matthew ^a   Chandramoorthy, Nandhini ^a   Debole, Michael ^c   Narayanan, Vijaykrishnan ^a  

^a The Pennsylvania State University   (United States)

^b INTEL CORPORATION   (United States)

^c IBM   (United States)

Author keywords

Dataflow process networks; Neuromorphic vision; Object recognition; System on chip; Visual saliency

Indexed keywords

BIOLOGICALLY INSPIRED; COMPUTATIONAL MODEL; GPU IMPLEMENTATION; HIGH ENERGY EFFICIENCY; IMAGE PROCESSING APPLICATIONS; MULTI CORE; MULTI-FPGA; NEUROMORPHIC; OBJECT DETECTION AND RECOGNITION; POTENTIAL BENEFITS; POWER EFFICIENCY; PROCESS NETWORKS; SYSTEM ON CHIPS; VISION ALGORITHMS; VISION APPLICATIONS; VISUAL PATHWAYS; VISUAL SALIENCY;

ALGORITHMS; APPLICATION SPECIFIC INTEGRATED CIRCUITS; COMPUTER ARCHITECTURE; ENERGY EFFICIENCY; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); OBJECT RECOGNITION; PROGRAMMABLE LOGIC CONTROLLERS;

MICROPROCESSOR CHIPS;

EID: 84864918550     PISSN: None     EISSN: 18826687     Source Type: Journal    
DOI: 10.2197/ipsjtsldm.5.71     Document Type: Article

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