no code implementations • 10 Feb 2025 • Giulia D Angelo, Victoria Clerico, Chiara Bartolozzi, Matej Hoffmann, P. Michael Furlong, Alexander Hadjiivanov
Active vision enables dynamic visual perception, offering an alternative to static feedforward architectures in computer vision, which rely on large datasets and high computational resources.
no code implementations • 18 Jan 2024 • Pao-Sheng Vincent Sun, Arren Glover, Chiara Bartolozzi, Arindam Basu
In this paper, we propose a new event-driven corner detection implementation tailored for edge computing devices, which requires much lower memory access than luvHarris while also improving accuracy.
no code implementations • 25 Oct 2023 • Simon F. Müller-Cleve, Fernando M. Quintana, Vittorio Fra, Pedro L. Galindo, Fernando Perez-Peña, Gianvito Urgese, Chiara Bartolozzi
Neuromorphic computing relies on spike-based, energy-efficient communication, inherently implying the need for conversion between real-valued (sensory) data and binary, sparse spiking representation.
1 code implementation • 10 Apr 2023 • Jason Yik, Korneel Van den Berghe, Douwe den Blanken, Younes Bouhadjar, Maxime Fabre, Paul Hueber, Weijie Ke, Mina A Khoei, Denis Kleyko, Noah Pacik-Nelson, Alessandro Pierro, Philipp Stratmann, Pao-Sheng Vincent Sun, Guangzhi Tang, Shenqi Wang, Biyan Zhou, Soikat Hasan Ahmed, George Vathakkattil Joseph, Benedetto Leto, Aurora Micheli, Anurag Kumar Mishra, Gregor Lenz, Tao Sun, Zergham Ahmed, Mahmoud Akl, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Petrut Bogdan, Sander Bohte, Sonia Buckley, Gert Cauwenberghs, Elisabetta Chicca, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Tobias Fischer, Jeremy Forest, Vittorio Fra, Steve Furber, P. Michael Furlong, William Gilpin, Aditya Gilra, Hector A. Gonzalez, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Shih-Chii Liu, Yao-Hong Liu, Haoyuan Ma, Rajit Manohar, Josep Maria Margarit-Taulé, Christian Mayr, Konstantinos Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayca Ozcelikkale, Priyadarshini Panda, Jongkil Park, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Samuel Schmidgall, Catherine Schuman, Jae-sun Seo, Sadique Sheik, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Stewart, Matthew Stewart, Terrence C. Stewart, Jonathan Timcheck, Nergis Tömen, Gianvito Urgese, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi
To address these shortcomings, we present NeuroBench: a benchmark framework for neuromorphic computing algorithms and systems.
no code implementations • 27 Feb 2023 • Marco Monforte, Luna Gava, Massimiliano Iacono, Arren Glover, Chiara Bartolozzi
Prediction skills can be crucial for the success of tasks where robots have limited time to act or joints actuation power.
no code implementations • 8 Dec 2022 • Stefano Panzeri, Ella Janotte, Alejandro Pequeño-Zurro, Jacopo Bonato, Chiara Bartolozzi
In the brain, information is encoded, transmitted and used to inform behaviour at the level of timing of action potentials distributed over population of neurons.
2 code implementations • 30 May 2022 • Simon F Muller-Cleve, Vittorio Fra, Lyes Khacef, Alejandro Pequeno-Zurro, Daniel Klepatsch, Evelina Forno, Diego G Ivanovich, Shavika Rastogi, Gianvito Urgese, Friedemann Zenke, Chiara Bartolozzi
Spatio-temporal pattern recognition is a fundamental ability of the brain which is required for numerous real-world activities.
no code implementations • 16 May 2022 • Luna Gava, Marco Monforte, Massimiliano Iacono, Chiara Bartolozzi, Arren Glover
Low latency and accuracy are fundamental requirements when vision is integrated in robots for high-speed interaction with targets, since they affect system reliability and stability.
no code implementations • 24 May 2021 • Arren Glover, Aiko Dinale, Leandro De Souza Rosa, Simeon Bamford, Chiara Bartolozzi
There have been a number of corner detection methods proposed for event cameras in the last years, since event-driven computer vision has become more accessible.
no code implementations • 1 Sep 2020 • Jingyue Zhao, Nicoletta Risi, Marco Monforte, Chiara Bartolozzi, Giacomo Indiveri, Elisa Donati
In this paper, we present a closed-loop motor controller implemented on mixed-signal analog-digital neuromorphic hardware using a spiking neural network.
no code implementations • 5 Jan 2020 • Marco Monforte, Ander Arriandiaga, Arren Glover, Chiara Bartolozzi
This paper investigates trajectory prediction for robotics, to improve the interaction of robots with moving targets, such as catching a bouncing ball.
no code implementations • 5 Dec 2019 • Ander Arriandiaga, Giovanni Morrone, Luca Pasa, Leonardo Badino, Chiara Bartolozzi
In order to overcome this limitation, we propose the use of event-driven cameras and exploit compression, high temporal resolution and low latency, for low cost and low latency motion feature extraction, going towards online embedded audio-visual speech processing.
no code implementations • 3 Dec 2019 • Arren Glover, Alan B. Stokes, Steve Furber, Chiara Bartolozzi
The Asynchronous Time-based Image Sensor (ATIS) and the Spiking Neural Network Architecture (SpiNNaker) are both neuromorphic technologies that "unconventionally" use binary spikes to represent information.
1 code implementation • 17 Apr 2019 • Guillermo Gallego, Tobi Delbruck, Garrick Orchard, Chiara Bartolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger, Andrew Davison, Joerg Conradt, Kostas Daniilidis, Davide Scaramuzza
Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur.
no code implementations • 27 Jun 2017 • Valentina Vasco, Arren Glover, Elias Mueggler, Davide Scaramuzza, Lorenzo Natale, Chiara Bartolozzi
In this paper, we propose a method for segmenting the motion of an independently moving object for event-driven cameras.