Searched for: subject%3A%22neuromorphic%22
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Şabanoğlu, Mahir (author)
An event-based camera enables capturing a video at a high temporal resolution, high dynamical range, reduced power consumption and minimal data bandwidth while the camera has minimal physical dimensions compared to a frame-based camera with the same vision properties. The limiting factor, however, of an event-based camera is the spatial...
master thesis 2023
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Kevin Shidqi, Kevin (author)
With recent breakthroughs in AI (Artificial Intelligence) technology, the impact of AI on society can be felt in various fields. The market for AI software, for example, reached a valuation of \$62 billion in 2022. A growing number of new computer architectures specialized in running these AI software were also developed. At first they were run...
master thesis 2022
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Verheyen, Jan (author)
Insects have — over millions of years of evolution — perfected many of the systems that roboticists aim to achieve; they can swiftly and robustly navigate through different environments under various conditions while at the same time being highly energy efficient. To reach this level of performance and efficiency one might want to look at and take...
master thesis 2022
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Buis, Jan Maarten (author)
Renewed interest in memory technologies such as memristors and ferroelectric devices can provide opportunities for traditional and non-traditional computing systems alike. To make versatile, reprogrammable AI hardware possible, neuromorphic systems are in need of a low-power, non-volatile and analog memory solution to store the weights of the...
master thesis 2022
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Stroobants, S. (author), Dupeyroux, J.J.G. (author), de Croon, G.C.H.E. (author)
ompelling evidence has been given for the high energy efficiency and update rates of neuromorphic processors, with performance beyond what standard Von Neumann architectures can achieve. Such promising features could be advantageous in critical embedded systems, especially in robotics. To date, the constraints inherent in robots (e.g., size and...
journal article 2022
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Dupeyroux, J.J.G. (author), Dinaux, Raoul (author), Wessendorp, Nikhil (author), de Croon, G.C.H.E. (author)
In this paper, we introduce the Obstacle Detection and Avoidance (ODA) Dataset for Drones, aiming at providing raw data obtained in a real indoor environment with sensors adapted for aerial robotics in the context of obstacle detection and avoidance. Our micro air vehicle (MAV) is equipped with the following sensors: (i) an event-based camera...
conference paper 2022
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Stroobants, S. (author), Dupeyroux, J.J.G. (author), de Croon, G.C.H.E. (author)
The great promises of neuromorphic sensing and processing for robotics have led researchers and engineers to investigate novel models for robust and reliable control of autonomous robots (navigation, obstacle detection and avoidance, etc.), especially for quadrotors in challenging contexts such as drone racing and aggressive maneuvers. Using...
conference paper 2022
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Verheyen, Jan K.N. (author), Dupeyroux, J.J.G. (author), de Croon, G.C.H.E. (author)
Insects have—over millions of years of evolution—perfected many of the systems that roboticists aim to achieve; they can swiftly and robustly navigate through different environments under various conditions while at the same time being highly energy efficient. To reach this level of performance and efficiency, one might want to look at and...
conference paper 2022
document
Chilakala, Koteswararao (author)
Diabetic Retinopathy (DR) is one of the leading causes of permanent vision loss. Its current prevalence is around 45 millions across the globe and is projected to 70 million by 2045. Most of the people with this disease condition belong to remote and low income settings. We can reduce this incidence, if quality medical care is accessible in...
master thesis 2021
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Gonzalez Alvarez, Marina (author)
Micro robotic airships offer significant advantages in terms of safety, mobility, and extended flight times. However, their highly restrictive weight constraints pose a major challenge regarding the available computational power to perform the required control tasks. Thus, spiking neural networks (SNNs) are a promising research direction. By...
master thesis 2021
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Wang, H. (author)
The human brain is a natural high-performance computing systemwith outstanding properties, e.g., ultra-low energy consumption, highly parallel information processing, suitability for solving complex tasks, and robustness. As such, numerous attempts have been made to devise neuromorphic systems able to achieve brain-akin computation abilities,...
doctoral thesis 2021
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Preetha Vijayan, Preetha (author)
In the recent past, real-time video processing using state-of-the-art deep neural networks (DNN) has achieved human-like accuracy but at the cost of high energy consumption, making them infeasible for edge device deployment. The energy consumed by running DNNs on hardware accelerators is dominated by the number of memory read/writes and...
master thesis 2021
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Kshirasagar, Shreya Sanjeev (author)
As we move towards edge computing, not only low power but concurrently, critical timing is demanded from the underlying hardware platform. Spiking neural networks ensure high performance and low power when run on specialized architectures like neuromorphic hardware. However, the techniques in use to configure these neural networks on massively...
master thesis 2021
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Dinaux, Raoul (author)
Micro Air Vehicles (MAVs) are able to support humans in dangerous operations, such as search and rescue operations at night on unknown terrain. These scenes require a great amount of autonomy from the MAV, as they are often radio and GPS-denied. As MAVs have limited computational resources and energy storage, onboard navigation tasks have to be...
master thesis 2021
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Iyer, Vishwas (author)
Significant work has been done in the field of computer vision focusing on learning and clustering methods. The use of improved learning methods has paved a way forward for researches to explore various theories to improve existing methods. One among various learning methods is Hierarchical learning which has showed impressive benefits and...
master thesis 2021
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Wang, H. (author), Cucu Laurenciu, N. (author), Jiang, Y. (author), Cotofana, S.D. (author)
Design and implementation of artificial neuromorphic systems able to provide brain akin computation and/or bio-compatible interfacing ability are crucial for understanding the human brain's complex functionality and unleashing brain-inspired computation's full potential. To this end, the realization of energy-efficient, low-area, and bio...
journal article 2021
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Parlevliet, Patricia P. (author), Kanaev, Andrey (author), Hung, Chou P. (author), Schweiger, Andreas (author), Gregory, Frederick D. (author), Benosman, Ryad (author), de Croon, G.C.H.E. (author), Gutfreund, Yoram (author), Lo, Chung Chuan (author), Moss, Cynthia F. (author)
Autonomous flight for large aircraft appears to be within our reach. However, launching autonomous systems for everyday missions still requires an immense interdisciplinary research effort supported by pointed policies and funding. We believe that concerted endeavors in the fields of neuroscience, mathematics, sensor physics, robotics, and...
journal article 2021
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Hagenaars, J.J. (author), Paredes-Vallés, Federico (author), Bohté, Sander M. (author), de Croon, G.C.H.E. (author)
Flying insects are capable of vision-based navigation in cluttered environments, reliably avoiding obstacles through fast and agile maneuvers, while being very efficient in the processing of visual stimuli. Meanwhile, autonomous micro air vehicles still lag far behind their biological counterparts, displaying inferior performance at a much...
journal article 2020
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Büller, Bas (author)
Spiking neural networks are notoriously hard to train because of their complex dynamics and sparse spiking signals. However, in part due to these properties, spiking neurons possess high computa- tional power and high theoretical energy efficiency. This thesis introduces an online, supervised, and gradient-based learning algorithm for spiking...
master thesis 2020
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Wang, H. (author), Cucu Laurenciu, N. (author), Jiang, Y. (author), Cotofana, S.D. (author)
Designing and implementing artificial systems that can be interfaced with the human brain or that can provide computational ability akin to brain's processing information efficient style is crucial for understanding human brain fundamental operating principles and to unleashing the full potential of brain-inspired computing. As basic neural...
conference paper 2020
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