MULTISPECTRAL INTELLIGENT VISION SYSTEM WITH EMBEDDED LOW-POWER NEURAL COMPUTING
Akronyymi
MISEL
Rahoitetun hankkeen kuvaus
"MISEL aims at bringing artificial intelligence to the edge computing (decisions made on-device) through a low-power bio-inspired vision system with multi-spectral sensing and in sensor spatio-temporal neuromorphic processing based on complex events. The science-to-technology breakthrough is the heterogeneous integration of a neuromorphic computing scheme featuring three different abstraction levels (cellular, cerebellar and cortex processors) with high-density memory arrays and adaptive photodetector technology for fast operation and energy efficiency. The context-aware, low power and distributed computation paradigm supported by MISEL is promising alternative to the current approach relying on massive-data transfers and large computational resources, e.g., workstations or cloud servers. This answers to the challenges and related scope presented in the Work Programme towards ""more complex, brain mimicking low power systems"" ""exploiting a wider range of biological principles from the hardware level up"" by introducing the human eye like adaptivity with cellular processor and the data fusion, learning, reasoning, and “conscious” decisions performed by the cortex.
The stand-alone system fabricated in MISEL will be tested on timely and challenging applications such as distinguishing birds from drones through their spatio-temporal flying signature, and scene anomaly detection from a mobile platform. From the technology development and industrialization point of view, MISEL includes the whole value chain: materials research for back-end of line (BEOL) processing-compatible densely-packed ferroelectric non-volatile memories (FeRAMs) and intensity adaptive photodetectors, novel neuromorphic computing algorithms and circuit implementations, and system level benchmarking. This is all in line with the challenge and scope of ""outperforming conventional SoA with relevant metric"" and benchmarking ""challenging end-to-end scenarios of use"" for industrial adaptation.
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Näytä enemmänAloitusvuosi
2021
Päättymisvuosi
2025
Myönnetty rahoitus
Kovilta Oy
990 000 €
Participant
LUNDS UNIVERSITET (SE)
270 000 €
Participant
LABORATOIRE NATIONAL DE METROLOGIE ET D'ESSAIS (FR)
420 990 €
Participant
GESELLSCHAFT FUR ANGEWANDTE MIKRO UND OPTOELEKTRONIK MIT BESCHRANKTERHAFTUNG AMO GMBH (DE)
350 625 €
Participant
UNIVERSIDAD DE SANTIAGO DE COMPOSTELA (ES)
653 301.25 €
Participant
BERGISCHE UNIVERSITAET WUPPERTAL (DE)
203 187.5 €
Participant
POLITECHNIKA LODZKA (PL)
348 750 €
Participant
FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V. (DE)
300 425 €
Participant
Myönnetty summa
4 969 451 €
Rahoittaja
Euroopan unioni
Rahoitusmuoto
Research and Innovation action
Puiteohjelma
Horizon 2020 Framework Programme
Haku
Ohjelman osa
EXCELLENT SCIENCE - Future and Emerging Technologies (FET) (5216 FET Proactive (5218 )
Aihe
Neuromorphic computing technologies (FETPROACT-09-2020Haun tunniste
H2020-FETPROACT-2020-01 Muut tiedot
Rahoituspäätöksen numero
101016734
Tunnistetut aiheet
artificial intelligence, machine learning