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Monolithic active pixel sensors (MAPS) produced in a 65 nm CMOS imaging technology are being investigated for applications in particle physics. The MAPS design has a small collection electrode characterized by an input capacitance of ~fF,…
Leveraging multi-modal fusion, especially between camera and LiDAR, has become essential for building accurate and robust 3D object detection systems for autonomous vehicles. Until recently, point decorating approaches, in which point…
One proposed component of the upcoming Deep Underground Neutrino Experiment (DUNE) near detector complex is a multi-purpose, magnetized, gaseous argon time projection chamber: the Multi-Purpose Detector (MPD). We explore the new-physics…
Following in the footsteps of the LHC, the Future Circular Collider (FCC) plans to be the next multi-generational collider project. In the first stage, FCC-ee will collide intense beams of electrons and positrons at centre of mass energies…
Muon colliders offer a compelling opportunity to explore the TeV scale and conduct precision tests of the Standard Model, all within a relatively compact geographical footprint. This paper introduces a new detector concept, MAIA (Muon…
The International Large Detector, ILD, is a detector concept for an experiment at a future high energy lepton collider. The detector has been optimised for precision physics in a range of energies from 90~GeV to about 1~TeV. ILD features a…
The CMS Beam Conditions and Radiation Monitoring System, BRM, will support beam tuning, protect the CMS detector from adverse beam conditions, and measure the accumulated dose close to or inside all sub-detectors. It is composed of…
Combining LiDAR and Camera-view data has become a common approach for 3D Object Detection. However, previous approaches combine the two input streams at a point-level, throwing away semantic information derived from camera features. In this…
Object detection has made impressive progress in recent years with the help of deep learning. However, state-of-the-art algorithms are both computation and memory intensive. Though many lightweight networks are developed for a trade-off…
Following the great success of Machine Learning (ML), especially Deep Neural Networks (DNNs), in many research domains in 2010s, several ML-based approaches were proposed for detection in large inverse linear problems, e.g., massive MIMO…
The emerging orthogonal time frequency space (OTFS) modulation technique has shown its superiority to the current orthogonal frequency division multiplexing (OFDM) scheme, in terms of its capabilities of exploiting full time-frequency…
The purpose of this project is to investigate the use of charge couple devices (CCDs) to detect electrons directly. This can be done in transmission electron microscopy (TEM) for electrons over 100 KeV, but for space plasma instruments,…
We present a phenomenology study probing pair production of supersymmetric charginos and neutralinos ("electroweakinos") with the vector boson fusion (VBF) topology in proton-proton collisions at CERN's Large Hadron Collider (LHC). In…
Recent approaches to develop infrared photodetectors characterized by high sensitivities, broadband spectral coverage, easy integration with silicon electronics and low cost have been based on hybrid structures of transition metal…
This part of the conference proceeding provides a detailed overview of cutting-edge advancements in detector technologies, focusing on their optimization, characterization, and applications in particle physics experiments. Building on the…
3D silicon detectors, in which the electrodes penetrate the sensor bulk perpendicular to the surface, have recently undergone a rapid development from R\&D over industrialisation to their first installation in a real high-energy-physics…
The Beam Dump Facility (BDF) project is a proposed general-purpose facility at CERN, dedicated to beam dump and fixed target experiments. In its initial phase, the facility is foreseen to be exploited by the Search for Hidden Particles…
Remote sensing object detection is a critical technology for real-world applications such as natural resource monitoring, traffic management, and UAV-based rescue. Detecting tiny objects in high-resolution aerial imagery remains challenging…
Depth estimation is a fundamental knowledge for autonomous systems that need to assess their own state and perceive the surrounding environment. Deep learning algorithms for depth estimation have gained significant interest in recent years,…
The physics aims at the proposed future high-energy linear $e^+e^-$ collider CLIC pose challenging demands on the performance of the detector system. In particular, the vertex and tracking detectors have to combine a spatial resolution of a…