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Wireless Sensor Network for Wildlife Tracking and Behavior Classification of Animals in Doñana
(IEEE Computer Society, 2016)
The study and monitoring of wildlife has always been a subject of great interest. Studying the behavior of wild animals is a difficult task due to the difficulties of tracking and classifying their actions. Nowadays, ...
Artículo
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Event-Driven Stereo Visual Tracking Algorithm to Solve Object Occlusion
(IEEE Computer Society, 2018)
Object tracking is a major problem for many computer vision applications, but it continues to be computationally expensive. The use of bio-inspired neuromorphic event-driven dynamic vision sensors (DVSs) has heralded ...
Ponencia
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ED-Scorbot: A Robotic test-bed Framework for FPGA-based Neuromorphic systems
(IEEE Computer Society, 2016)
Neuromorphic engineering is a growing and promising discipline nowadays. Neuro-inspiration and brain understanding applied to solve engineering problems is boosting new architectures, solutions and products today. The ...
Ponencia
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Frames-to-AER efficiency study based on CPUs Performance Counters
(IEEE Computer Society, 2010)
Image processing in digital computer systems usually considers the visual information as a sequence of frames. These frames are from photographs that capture reality for a short period of time. They are renewed and ...
Ponencia
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A signed spatial contrast event spike retina chip
(IEEE Computer Society, 2010)
Reported AER (Address Event Representation) contrast retinae perform a contrast computation based on the ratio between a pixel's local light intensity and a spatially weighted average of its neighbourhood. This results in ...
Artículo
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mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks
(Elsevier, 2013)
Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, ...
Ponencia
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Design of adaptive nano/CMOS neural architectures
(IEEE Computer Society, 2012)
Memristive devices are a promising technology to implement dense learning synapse arrays emulating the high memory capacity and connectivity of biological brains. Recently, the implementation of STDP learning in memristive ...
Ponencia
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Determination of a Power-Saving Method for Real- Time Wireless Sensor Networks
(IEEE Computer Society, 2010)
In wireless sensor networks, battery life is a key resource that must be conserved as much as possible. Nowadays, the main way of achieve power saving in this type of circuits is to implement low-power RF (Radio Frequency) ...