Related papers: Automatic Event Recognition Employing Optically Ex…

Event-based vision sensors achieve up to three orders of magnitude better speed vs. power consumption trade off in high-speed control of UAVs compared to conventional image sensors. Event-based cameras produce a sparse stream of events that…

Facial Expression Recognition (FER) is an active research domain that has shown great progress recently, notably thanks to the use of large deep learning models. However, such approaches are particularly energy intensive, which makes their…

Event cameras are neuromorphic sensors that capture asynchronous and sparse event stream when per-pixel brightness changes. The state-of-the-art processing methods for event signals typically aggregate events into a frame or a grid.…

We present a novel quantum phenomenon named electromagnetically induced entanglement in the conventional Lambda-type three-level atomic system driven by a strong pump field and a relatively weak probe field. Nearly perfect entanglement…

Facial Expression Recognition is a vital research topic in most fields ranging from artificial intelligence and gaming to Human-Computer Interaction (HCI) and Psychology. This paper proposes a hybrid model for Facial Expression recognition,…

We propose a novel approach to the important fundamental problem of detecting weak optical fields at the few photon level. The ability to detect with high efficiency (>99%), and to distinguish the number of photons in a given time interval…

Spin-polarised atomic ensembles probed by light based on the Faraday interaction are a versatile platform for numerous applications in quantum metrology and quantum information processing. Here we consider an ensemble of Alkali atoms that…

In this paper a new formulation of event recognition task is examined: it is required to predict event categories in a gallery of images, for which albums (groups of photos corresponding to a single event) are unknown. We propose the novel…

Understanding and controlling decoherence in open quantum systems is of fundamental interest in science, while achieving long coherence times is critical for quantum information processing. Although great progress was made for individual,…

The active efficient coding (AEC) framework parsimoniously explains the joint development of visual processing and eye movements, e.g., the emergence of binocular disparity selective neurons and fusional vergence, the disjunctive eye…

An event camera detects per-pixel intensity difference and produces asynchronous event stream with low latency, high dynamic range, and low power consumption. As a trade-off, the event camera has low spatial resolution. We propose an…

Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and…

A new algorithm, "HiER-leap", is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or…

Event camera is a novel bio-inspired vision sensor that outputs event stream. In this paper, we propose a novel data fusion algorithm called EAS to fuse conventional intensity images with the event stream. The fusion result is applied to…

In this work, we consider a three-level ladder-type atom driven by a coherent field, inspired by the experimental work of Gasparinetti et al. [Phys. Rev. A 100, 033802 (2019)]. When driven on two-photon resonance, the atom is excited into…

As artificial intelligence (AI) systems become increasingly embedded in our daily life, the ability to recognize and adapt to human emotions is essential for effective human-computer interaction. Facial expression recognition (FER) provides…

Entangled two-photon absorption (ETPA) may be a viable technique to continuously drive an excited state population in plasma for high-bandwidth spectroscopy measurements of localized plasma turbulence or impurity density. Classical…

With the growing adoption of autonomous driving, the advancement of sensor technology is crucial for ensuring safety and reliable operation. Sensor fusion techniques that combine multiple sensors such as LiDAR, radar, and cameras have…

Multilayer Extreme Learning Machine (ML-ELM) and its variants have proven to be an effective technique for the classification of different natural signals such as audio, video, acoustic and images. In this paper, a Hybrid Multilayer Extreme…

Single-photon light detection and ranging (LiDAR) is a key technology for depth imaging through complex environments. Despite recent advances, an open challenge is the ability to isolate the LiDAR signal from other spurious sources…