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3D occupancy becomes a promising perception representation for autonomous driving to model the surrounding environment at a fine-grained scale. However, it remains challenging to efficiently aggregate 3D occupancy over time across multiple…

Robust 3D occupancy prediction is essential for autonomous driving, particularly under adverse weather conditions where traditional vision-only systems struggle. While the fusion of surround-view 4D radar and cameras offers a promising…

There are scientific and technological needs to improve the co-phasing of the primary mirrors of segmented telescopes. We have developed a methodology for using the wavefront sensor of an adaptive optics (AO) system to disentangle the phase…

The Lick Observatory's Shane 3-meter telescope has been upgraded with a new infrared instrument (ShARCS - Shane Adaptive optics infraRed Camera and Spectrograph) and dual-deformable mirror adaptive optics (AO) system (ShaneAO). We present…

In ground-based astronomy, Adaptive Optics (AO) is a pivotal technique, engineered to correct wavefront phase distortions and thereby enhance the quality of the observed images. Integral to an AO system is the wavefront sensor (WFS), which…

Direct imaging is an active research topic in astronomy for the detection and the characterization of young sub-stellar objects. The very high contrast between the host star and its companions makes the observations particularly…

Context. Adaptive optics (AO) is now a tool commonly deployed in astronomy. The real time correction of the atmospheric turbulence that AO enables allows telescopes to perform close to the diffraction limit at the core of their point spread…

A latent world model may achieve accurate short-horizon prediction while still inducing a latent space that is poorly aligned with planning. A key issue is spatiotemporal mismatch: these models are often trained with local predictive…

This paper introduces RaCo, a lightweight neural network designed to learn robust and versatile keypoints suitable for a variety of 3D computer vision tasks. The model integrates three key components: the repeatable keypoint detector, a…

Trajectory Optimization (TO) and Reinforcement Learning (RL) offer complementary strengths for solving optimal control problems. TO efficiently computes locally optimal solutions but can struggle with non-convexity, while RL is more robust…

Optical coherence tomography (OCT), a commonly used retinal imaging modality, plays a central role in retinal disease diagnosis by providing high-resolution visualization of retinal layers. While deep learning (DL) has achieved expert-level…

Exoplanet direct imaging allows us to directly probe and characterize an exoplanet's atmosphere, searching for signs of life in its atmospheric signatures. Directly imaging an Earth-like planet around a Sun-like star requires reaching…

Optical proximity correction (OPC) is a widely-used resolution enhancement technique (RET) for printability optimization. Recently, rigorous numerical optimization and fast machine learning are the research focus of OPC in both academia and…

Developing scalable, fault-tolerant atomic quantum processors requires precise control over large arrays of optical beams. This remains a major challenge due to inherent imperfections in classical control hardware, such as inter-channel…

Radiative transfer modelling is part of many astrophysical simulations and is used to make synthetic observations and to assist analysis of observations. We concentrate on the modelling of the radio lines emitted by the interstellar medium.…

Current surgical procedures for spinal cord tumors lack in vivo high-resolution, high-speed multifunctional imaging systems, posing challenges for precise tumor resection and intraoperative decision-making. This study introduces the Fast…

Optical imperfections, misalignments, aberrations, and even dust can significantly limit sensitivity in high-contrast imaging systems such as coronagraphs. An upstream deformable mirror (DM) in the pupil can be used to correct or compensate…

Cognitive radio (CR) is a key enabler realizing future networks to achieve higher spectral efficiency by allowing spectrum sharing between different wireless networks. It is important to explore whether spectrum access opportunities are…

This work addresses the ecological-adaptive cruise control problem for connected electric vehicles by a computationally efficient robust control strategy. The problem is formulated in the space-domain with a realistic description of the…

The development of spaceborne coronagraphic technology is of paramount importance to the detection of habitable exoplanets in visible light. In space, coronagraphs are able to bypass the limitations imposed by the atmosphere to reach deeper…