12 papers · ranked by Valyu relevance
Mateusz Pabian, Dominik Rzepka, Mirosław Pawlak, Marek Miśkowicz + 1 more
'Ryszard Sroka'] Event-driven systems can operate either on discrete-time event streams or on analog signals transformed into the event domain by a predefined encoding scheme. This paper studies the problem of optimal event-based signal encoding if data are to be processed by a machine learning model, such as the…
Martin V. Butz
This paper proposes how various disciplinary theories of cognition may be combined into a unifying, sub-symbolic, computational theory of cognition. The following theories are considered for integration: psychological theories, including the theory of event coding, event segmentation theory, the theory of anticipatory…
Kamilya Smagulova, Ahmed Elsheikh, Diego A. Silva, Mohammed E. Fouda + 1 more
Autonomous driving has the potential to enhance driving comfort and accessibility, reduce accidents, and improve road safety, with vision sensors playing a key role in enabling vehicle autonomy. Among existing sensors, event-based cameras offer advantages such as a high dynamic range, low power consumption, and…
Zhuowen Zou, Haleh Alimohamadi, Yeseong Kim, M. Hassan Najafi + 2 more
'Narayan Srinivasa' 'Mohsen Imani'] Brain-inspired computing models have shown great potential to outperform today's deep learning solutions in terms of robustness and energy efficiency. Particularly, Hyper-Dimensional Computing (HDC) has shown promising results in enabling efficient and robust cognitive learning. In…
Simon F. Müller-Cleve, Vittorio Fra, Lyes Khacef, Alejandro Pequeño-Zurro + 7 more
'Alejandro Pequeño-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. Recent deep learning approaches…
Prafull Purohit, Rajit Manohar
In conventional frame-based image sensors, every pixel records brightness information and sends this information to a receiver serially in a scanning fashion. This full-frame readout approach suffers from high bandwidth requirements and increased power consumption with the increasing size of the pixel array.…
Hanyu Wang, Jiangtao Xu, Zhiyuan Gao, Chengye Lu + 2 more
'Jianguo Ma'] A new multiple orientation event-based neurobiological recognition system is proposed by integrating recognition and tracking function in this paper, which is used for asynchronous address-event representation (AER) image sensors. The characteristic of this system has been enriched to recognize the…
Guang Chen, Hu Cao, Canbo Ye, Zhenyan Zhang + 6 more
'Zhongnan Qu' 'Jörg Conradt' 'Florian Röhrbein' 'Alois Knoll'] Neuromorphic vision sensors are bio-inspired cameras that naturally capture the dynamics of a scene with ultra-low latency, filtering out redundant information with low power consumption. Few works are addressing the object detection with this sensor. In…
Diego A. Silva, Kamilya Smagulova, Ahmed Elsheikh, Mohammed E. Fouda + 1 more
'Ahmed M. Eltawil'] Object detection plays a crucial role in various cutting-edge applications, such as autonomous vehicles and advanced robotics systems, primarily relying on conventional frame-based RGB sensors. However, these sensors face challenges such as motion blur and poor performance under extreme lighting…
Ionut Schiopu, Radu Ciprian Bilcu, Ittetsu Taniguchi, Jinjia Zhou + 1 more
'Xin Jin'] The event sensor provides high temporal resolution and generates large amounts of raw event data. Efficient low-complexity coding solutions are required for integration into low-power event-processing chips with limited memory. In this paper, a novel lossless compression method is proposed for encoding the…
Claudio Cimarelli, Jose Andres Millan-Romera, Holger Voos, Jose Luis Sanchez-Lopez + 1 more
Event-based (neuromorphic) cameras depart from frame-based sensing by reporting asynchronous per-pixel brightness changes. This produces sparse, low-latency data streams with extreme temporal resolution but demands new processing paradigms. In this survey, we systematically examine neuromorphic vision along three main…
Jayasingam Adhuran, Nabeel Khan, Maria G. Martini, Jean Chamberlain Chedjou
'Jean Chamberlain Chedjou'] Neuromorphic Vision Sensors (NVSs) are emerging sensors that acquire visual information asynchronously when changes occur in the scene. Their advantages versus synchronous capturing (frame-based video) include a low power consumption, a high dynamic range, an extremely high temporal…