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The primary objective of this work is the determination of fluences and characteristics of fast neutrons, other hadrons, and highly ionizing particles in the environment of the MoEDAL experiment at the Large Hadron Collider. These particles…
Pixel detectors for precise particle tracking in high energy physics have been developed to a level of maturity during the past decade. Three of the LHC detectors will use vertex detectors close to the interaction point based on the hybrid…
Reformulating computer vision problems over Riemannian manifolds has demonstrated superior performance in various computer vision applications. This is because visual data often forms a special structure lying on a lower dimensional space…
When localizing and detecting 3D objects for autonomous driving scenes, obtaining information from multiple sensor (e.g. camera, LIDAR) typically increases the robustness of 3D detectors. However, the efficient and effective fusion of…
The core of our approach, Pixel Consensus Voting, is a framework for instance segmentation based on the Generalized Hough transform. Pixels cast discretized, probabilistic votes for the likely regions that contain instance centroids. At the…
In this paper we study the application of convolutional neural networks for jointly detecting objects depicted in still images and estimating their 3D pose. We identify different feature representations of oriented objects, and energies…
Change detection and irregular object extraction in 3D point clouds is a challenging task that is of high importance not only for autonomous navigation but also for updating existing digital twin models of various industrial environments.…
Semiconductor pixel detectors offer features for the detection of radiation which are interesting for particle physics detectors as well as for imaging e.g. in biomedical applications (radiography, autoradiography, protein crystallography)…
3D object detection and pose estimation has been studied extensively in recent decades for its potential applications in robotics. However, there still remains challenges when we aim at detecting multiple objects while retaining low false…
Clustering algorithms are one of the main analytical methods to detect patterns in unlabeled data. Existing clustering methods typically treat samples in a dataset as points in a metric space and compute distances to group together similar…
The demands on detectors for particle detection as well as for medical and astronomical X-ray imaging are continuously pushing the development of novel pixel detectors. The state of the art in pixel detector technology to date are hybrid…
The design of a detector system comprised of four silicon sensors bump-bonded to Timepix4 ASICs is described together with its data acquisition system, operational infrastructure, and dedicated software. The spatial and temporal performance…
Novel event-based electron detector platforms provide an avenue to extend the temporal resolution of electron microscopy into the ultrafast domain. Here, we characterize the timing accuracy of a detector based on a TimePix3 architecture…
While designed primarily for X-ray imaging applications, the Medipix3 ASIC can also be used for charged-particle tracking. In this work, results from a beam test at the CERN SPS with irradiated and non-irradiated sensors are presented and…
Recent camera-based 3D object detection methods have introduced sequential frames to improve the detection performance hoping that multiple frames would mitigate the large depth estimation error. Despite improved detection performance,…
High-resolution 3D point clouds are highly effective for detecting subtle structural anomalies in industrial inspection. However, their dense and irregular nature imposes significant challenges, including high computational cost,…
Co-localization is the problem of localizing objects of the same class using only the set of images that contain them. This is a challenging task because the object detector must be built without negative examples that can lead to more…
The Timepix particle tracking telescope has been developed as part of the LHCb VELO Upgrade project, supported by the Medipix Collaboration and the AIDA framework. It is a primary piece of infrastructure for the VELO Upgrade project and is…
A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from…
With the ultimate goal of developing a pixel-based readout for a TPC at the ILC, a GridPix readout system consisting of one Timepix3 chip with an integrated amplification grid was embedded in a prototype detector. The performance was…