Now showing items 1-10 of 33
Opening the Black Box: Explaining the Process of Basing a Health Recommender System on the I-Change Behavioral Change Model
(IEEE Computer Society, 2019)
Recommender systems are gaining traction in healthcare because they can tailor recommendations based on users' feedback concerning their appreciation of previous health-related messages. However, recommender systems are ...
Asynchronous Spiking Neurons, the Natural Key to Exploit Temporal Sparsity
(IEEE Computer Society, 2019)
Inference of Deep Neural Networks for stream signal (Video/Audio) processing in edge devices is still challenging. Unlike the most state of the art inference engines which are efficient for static signals, our brain is ...
Event-driven implementation of deep spiking convolutional neural networks for supervised classification using the SpiNNaker neuromorphic platform
Neural networks have enabled great advances in recent times due mainly to improved parallel computing capabilities in accordance to Moore’s Law, which allowed reducing the time needed for the parameter learning of complex, ...
Neocortical frame-free vision sensing and processing through scalable Spiking ConvNet hardware
(IEEE Computer Society, 2010)
This paper summarizes how Convolutional Neural Networks (ConvNets) can be implemented in hardware using Spiking neural network Address-Event-Representation (AER) technology, for sophisticated pattern and object recognition ...
A 1.5 ns OFF/ON Switching-Time Voltage-Mode LVDS Driver/Receiver Pair for Asynchronous AER Bit-Serial Chip Grid Links With Up to 40 Times Event-Rate Dependent Power Savings
(IEEE Computer Society, 2013)
This paper presents a low power fast ON/OFF switchable voltage mode implementation of a driver/receiver pair intended to be used in high speed bit-serial Low Voltage Differential Signaling (LVDS) Address Event ...
A 32 x 32 Pixel Convolution Processor Chip for Address Event Vision Sensors With 155 ns Event Latency and 20 Meps Throughput
(IEEE Computer Society, 2011)
This paper describes a convolution chip for event-driven vision sensing and processing systems. As opposed to conventional frame-constraint vision systems, in event-driven vision there is no need for frames. In frame-free ...
A memristive nanoparticle/organic hybrid synapstor for neuro-inspired computing.
A large effort is devoted to the research of new computing paradigms associated with innovative nanotechnologies that should complement and/or propose alternative solutions to the classical Von Neumann/CMOS (complementary ...
A Precise CMOS Mismatch Model for Analog Design from Weak to Strong Inversion
(IEEE Computer Society, 2004)
A five parameter mismatch model continuos from weak to strong inversion is presented. The model is an extension of a previously reported one valid in the strong inversion region . A mismatch characterization of NMOS ...
High-Speed Character Recognition System based on a complex hierarchical AER architecture
(IEEE Computer Society, 2008)
In this paper we briefly summarize the fundamental properties of spikes processing applied to artificial vision systems. This sensing and processing technology is capable of very high speed throughput, because it does ...
An Intrinsic Method for Fast Parameter Update on the SpiNNaker Platform
(IEEE Computer Society, 2018)
Neuromorphic Computing or Spiking (also called Event-Driven) Neural Systems are becoming of high interest as they potentially allow for lower power hardware computing platforms, where power consumption is data driven. ...