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Efficient Spike-Driven Learning With Dendritic Event-Based Processing [PDF]
Frontiers in Neuroscience, 2021 A critical challenge in neuromorphic computing is to present computationally efficient algorithms of learning. When implementing gradient-based learning, error information must be routed through the network, such that each neuron knows its contribution ...
Shuangming Yang +5 more
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Event-based media processing and analysis: A survey of the literature [PDF]
Image and Vision Computing, 2016 Research on event-based processing and analysis of media is receiving an increasing attention from the scientific community due to its relevance for an abundance of applications, from consumer video management and video surveillance to lifelogging and social media.
Vasileios Mezaris +2 more
exaly +6 more sources
EventEpi-A natural language processing framework for event-based surveillance.
PLoS Computational Biology, 2020 According to the World Health Organization (WHO), around 60% of all outbreaks are detected using informal sources. In many public health institutes, including the WHO and the Robert Koch Institute (RKI), dedicated groups of public health agents sift ...
Auss Abbood +3 more
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Bonsai: An event-based framework for processing and controlling data streams [PDF]
Frontiers in Neuroinformatics, 2015 The design of modern scientific experiments requires the control and monitoring of many different data streams. However, the serial execution of programming instructions in a computer makes it a challenge to develop software that can deal with the ...
Gonçalo eLopes +15 more
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IEEE Access, 2018 Event processing systems serve as a middleware between the Internet of Things (IoT) and the application layer by allowing users to subscribe to events of interest. Due to the increase of multimedia IoT devices (i.e.
Asra Aslam, Edward Curry
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Distributed Event-Driven Serverless Platform for Multicluster IoT Environments [PDF]
SensorsIn modern smart city and IoT environments, diverse sensors for traffic management, environmental monitoring, and energy systems continuously generate large volumes of heterogeneous events in real time.
Hyungwoo Ju, Jangwon Seo, Younghan Kim
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Event-based Signal Processing for Radioisotope Identification [PDF]
2020 6th International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP), 2020 This paper identifies the problem of unnecessary high power overhead of the conventional frame-based radioisotope identification process and proposes an event-based signal processing process to address the problem established. It also presents the design flow of the neuromorphic processor.
Xiaoyu Huang +8 more
openaire +2 more sources
Revisiting Batch Normalization for Training Low-Latency Deep Spiking Neural Networks From Scratch
Frontiers in Neuroscience, 2021 Spiking Neural Networks (SNNs) have recently emerged as an alternative to deep learning owing to sparse, asynchronous and binary event (or spike) driven processing, that can yield huge energy efficiency benefits on neuromorphic hardware.
Youngeun Kim, Priyadarshini Panda
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Sharing leaky-integrate-and-fire neurons for memory-efficient spiking neural networks
Frontiers in Neuroscience, 2023 Spiking Neural Networks (SNNs) have gained increasing attention as energy-efficient neural networks owing to their binary and asynchronous computation.
Youngeun Kim +4 more
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Velocity and Color Estimation Using Event-Based Clustering
Sensors, 2023 Event-based clustering provides a low-power embedded solution for low-level feature extraction in a scene. The algorithm utilizes the non-uniform sampling capability of event-based image sensors to measure local intensity variations within a scene ...
Xavier Lesage +3 more
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