no code implementations • 1 Oct 2023 • Ole Richter, Chenxi Wu, Adrian M. Whatley, German Köstinger, Carsten Nielsen, Ning Qiao, Giacomo Indiveri
With the remarkable progress that technology has made, the need for processing data near the sensors at the edge has increased dramatically.
1 code implementation • 4 May 2023 • Lexuan Xu, Guang Hua, Haijian Zhang, Lei Yu, Ning Qiao
Most of the artificial lights fluctuate in response to the grid's alternating current and exhibit subtle variations in terms of both intensity and spectrum, providing the potential to estimate the Electric Network Frequency (ENF) from conventional frame-based videos.
no code implementations • 13 Apr 2023 • Ole Richter, Yannan Xing, Michele De Marchi, Carsten Nielsen, Merkourios Katsimpris, Roberto Cattaneo, Yudi Ren, Qian Liu, Sadique Sheik, Tugba Demirci, Ning Qiao
This is due to the increasing number of smart devices that require sensory processing for their application on the edge.
1 code implementation • CVPR 2023 • Lexuan Xu, Guang Hua, Haijian Zhang, Lei Yu, Ning Qiao
Most of the artificial lights fluctuate in response to the grid's alternating current and exhibit subtle variations in terms of both intensity and spectrum, providing the potential to estimate the Electric Network Frequency (ENF) from conventional frame-based videos.
1 code implementation • CVPR 2022 • Wei Liao, Xiang Zhang, Lei Yu, ShiJie Lin, Wen Yang, Ning Qiao
This paper addresses this problem by leveraging the merits of both events and frames, leading to a fusion-based SAI (EF-SAI) that performs consistently under the different densities of occlusions.
no code implementations • 25 Jun 2020 • Arianna Rubino, Can Livanelioglu, Ning Qiao, Melika Payvand, Giacomo Indiveri
Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications.
no code implementations • 19 Aug 2019 • Ning Qiao, Giacomo Inidveri
As processes continue to scale aggressively, the design of deep sub-micron, mixed-signal design is becoming more and more challenging.
Emerging Technologies
no code implementations • 18 Aug 2019 • Ning Qiao, Giacomo Indiveri
Developing mixed-signal analog-digital neuromorphic circuits in advanced scaled processes poses significant design challenges.
Emerging Technologies
no code implementations • 25 Oct 2018 • Sebastian Glatz, Julien N. P. Martel, Raphaela Kreiser, Ning Qiao, Yulia Sandamirskaya
In this paper, we present a spiking neural network architecture that uses sensory feedback to control rotational velocity of a robotic vehicle.
no code implementations • 23 May 2018 • Chetan Singh Thakur, Jamal Molin, Gert Cauwenberghs, Giacomo Indiveri, Kundan Kumar, Ning Qiao, Johannes Schemmel, Runchun Wang, Elisabetta Chicca, Jennifer Olson Hasler, Jae-sun Seo, Shimeng Yu, Yu Cao, André van Schaik, Ralph Etienne-Cummings
Neuromorphic engineering (NE) encompasses a diverse range of approaches to information processing that are inspired by neurobiological systems, and this feature distinguishes neuromorphic systems from conventional computing systems.
no code implementations • 14 Aug 2017 • Saber Moradi, Ning Qiao, Fabio Stefanini, Giacomo Indiveri
However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements.