Related papers: Hydra: Computer Vision for Data Quality Monitoring
Large language models are increasingly used for code generation, but many generated programs fail to compile, a prerequisite for further correctness checks such as unit tests. Existing solutions for repairing static errors are costly in…
Hydra is a full-scale industrial CFD application used for the design of turbomachinery at Rolls Royce plc. It consists of over 300 parallel loops with a code base exceeding 50K lines and is capable of performing complex simulations over…
The Hall-D Online Skim System (HOSS) was developed to simultaneously solve two issues for the high intensity GlueX experiment. One was to parallelize the writing of raw data files to disk in order to improve bandwidth. The other was to…
Human Activity Recognition (HAR) systems aim to understand human behaviour and assign a label to each action, attracting significant attention in computer vision due to their wide range of applications. HAR can leverage various data…
Low-cost, vision-centric 3D perception systems for autonomous driving have made significant progress in recent years, narrowing the gap to expensive LiDAR-based methods. The primary challenge in becoming a fully reliable alternative lies in…
The behaviors of deep neural networks (DNNs) are notoriously resistant to human interpretations. In this paper, we propose Hypergradient Data Relevance Analysis, or HYDRA, which interprets the predictions made by DNNs as effects of their…
We propose a design-time framework (named HYDRA-C) for integrating security tasks into partitioned real-time systems (RTS) running on multicore platforms. Our goal is to opportunistically execute security monitoring mechanisms in a…
In the past few years, augmented reality (AR) and virtual reality (VR) technologies have experienced terrific improvements in both accessibility and hardware capabilities, encouraging the application of these devices across various domains.…
Many modern video processing pipelines rely on edge-aware (EA) filtering methods. However, recent high-quality methods are challenging to run in real-time on embedded hardware due to their computational load. To this end, we propose an…
Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrated data analysis plays a…
3D spatial perception is the problem of building and maintaining an actionable and persistent representation of the environment in real-time using sensor data and prior knowledge. Despite the fast-paced progress in robot perception, most…
Dataflow architectures are growing in popularity due to their potential to mitigate the challenges posed by the memory wall inherent to the Von Neumann architecture. At the same time, high-level synthesis (HLS) has demonstrated its efficacy…
Independently exploring unknown spaces or finding objects in an indoor environment is a daily but challenging task for visually impaired people. However, common 2D assistive systems lack depth relationships between various objects,…
We introduce HIDRO-VQA, a no-reference (NR) video quality assessment model designed to provide precise quality evaluations of High Dynamic Range (HDR) videos. HDR videos exhibit a broader spectrum of luminance, detail, and color than…
Fully understanding performance is a growing challenge when building next-generation cloud systems. Often these systems build on next-generation hardware, and evaluation in realistic physical testbeds is out of reach. Even when physical…
Mesh quality assessment (MQA) models play a critical role in the design, optimization, and evaluation of mesh operation systems in a wide variety of applications. Current MQA models, whether model-based methods using topology-aware features…
We have developed a framework for crisis response and management that incorporates the latest technologies in computer vision (CV), inland flood prediction, damage assessment and data visualization. The framework uses data collected before,…
A fast, efficient and comprehensive monitoring system is a vital part of any HEP experiment. This paper describes the software framework that will be used during ATLAS data taking to monitor the state of the data acquisition and the quality…
The study group on data preservation in high energy physics, DPHEP, is moving to a new collaboration structure, which will focus on the implementation of preservation projects, such as those described in the group's large scale report…
Multiple human tracking (MHT) is a fundamental task in many computer vision applications. Appearance-based approaches, primarily formulated on RGB data, are constrained and affected by problems arising from occlusions and/or illumination…