相关论文: Realizing Fully-Integrated, Low-Power, Event-Based…

Brain-inspired spiking neural networks (SNNs) have gained prominence in the field of neuromorphic computing owing to their low energy consumption during feedforward inference on neuromorphic hardware. However, it remains an open challenge…

Event-based data are commonly encountered in edge computing environments where efficiency and low latency are critical. To interface with such data and leverage their rich temporal features, we propose a causal spatiotemporal convolutional…

The joint progress of artificial neural networks (ANNs) and domain specific hardware accelerators such as GPUs and TPUs took over many domains of machine learning research. This development is accompanied by a rapid growth of the required…

As an alternative sensing paradigm, dynamic vision sensors (DVS) have been recently explored to tackle scenarios where conventional sensors result in high data rate and processing time. This paper presents a hybrid event-frame approach for…

Underwater environments impose severe constraints on conventional imaging systems and demand solutions that balance high-quality sensing with strict resource efficiency. While emerging event cameras offer a promising alternative, their…

This paper presents a low-cost eye-tracker aimed at carrying out tests based on a Visual Paired Comparison protocol for the early detection of Mild Cognitive Impairment. The proposed eye-tracking system is based on machine learning…

Clinical-grade wearable sleep monitoring is a challenging problem since it requires concurrently monitoring brain activity, eye movement, muscle activity, cardio-respiratory features and gross body movements. This requires multiple sensors…

Wearable and implantable healthcare sensors are pivotal for real-time patient monitoring but face critical challenges in power efficiency, data security, and signal noise. This paper introduces a novel platform that leverages hardware noise…

Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent parallelism make neuromorphic computing a promising paradigm…

We present a set of results obtained with an innovative eye-tracker based on magnetic dipole localization by means of an array of magnetoresistive sensors. The system tracks both head and eye movements with a high rate (100-200 Sa/s) and in…

Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. Hence, researchers have been exploring different energy-efficient solutions such as near-sensor processing, in-sensor…

Driven by the progress in efficient embedded processing, there is an accelerating trend toward running machine learning models directly on wearable Brain-Machine Interfaces (BMIs) to improve portability and privacy and maximize battery…

Delirium, an acute confusional state, is a common occurrence in Intensive Care Units (ICUs). Patients who develop delirium have globally worse outcomes than those who do not and thus the diagnosis of delirium is of importance. Current…

Saccades are extremely rapid movements of both eyes that occur simultaneously, typically observed when an individual shifts their focus from one object to another. These movements are among the swiftest produced by humans and possess the…

Various methods have been proposed for authentication, including password or pattern drawing, which is clearly visible on personal electronic devices. However, these methods of authentication are more vulnerable, as passwords and cards can…

Event cameras are an interesting visual exteroceptive sensor that reacts to brightness changes rather than integrating absolute image intensities. Owing to this design, the sensor exhibits strong performance in situations of challenging…

Recent advances in memory technologies, devices and materials have shown great potential for integration into neuromorphic electronic systems. However, a significant gap remains between the development of these materials and the realization…

Atrial fibrillation (AF) is a common arrhythmia and major risk factor for cardiovascular complications. While commercially available devices and supporting Artificial Intelligence (AI) algorithms exist for reliable detection of AF, the…

Vision-based localization is a cost-effective and thus attractive solution for many intelligent mobile platforms. However, its accuracy and especially robustness still suffer from low illumination conditions, illumination changes, and…

The growing need for intelligent, adaptive, and energy-efficient autonomous systems across fields such as robotics, mobile agents (e.g., UAVs), and self-driving vehicles is driving interest in neuromorphic computing. By drawing inspiration…