相关论文: Transformer-Based Approach to Enhance Positron Tra…
Understanding trajectory diversity is a fundamental aspect of addressing practical traffic tasks. However, capturing the diversity of trajectories presents challenges, particularly with traditional machine learning and recurrent neural…
Evaluating lesion progression and treatment response via longitudinal lesion tracking plays a critical role in clinical practice. Automated approaches for this task are motivated by prohibitive labor costs and time consumption when lesion…
This paper describes applications of two neural networks to improve drift chamber position measurements. One network calculates a data-driven estimate of the drift cell time-to-distance relationship that is conventionally estimated by a…
Region proposal based methods like R-CNN and Faster R-CNN models have proven to be extremely successful in object detection and segmentation tasks. Recently, Transformers have also gained popularity in the domain of Computer Vision, and are…
Triple-GEM detectors for the GE2/1 and ME0 stations of the endcap muon system for the Phase-2 upgrade of the CMS Experiment have been operated in a test beam to measure their efficiency and spatial resolution, together with a high spatial…
In many spatial trajectory-based applications, it is necessary to map raw trajectory data points onto road networks in digital maps, which is commonly referred to as a map-matching process. While most previous map-matching methods have…
Stellar spectra emulators often rely on large grids and tend to reach a plateau in emulation accuracy, leading to significant systematic errors when inferring stellar properties. Our study explores the use of Transformer models to capture…
This study investigates artifact detection in clinical photoplethysmogram signals using Transformer-based models. Recent findings have shown that in detecting artifacts from the Pediatric Critical Care Unit at CHU Sainte-Justine (CHUSJ),…
Next-generation wireless networks are expected to leverage multi-modal data sources to execute various wireless communication tasks such as beamforming and blockage prediction with situational-awareness. To do so, multi-modal transformers…
The deployment of transformers for visual object tracking has shown state-of-the-art results on several benchmarks. However, the transformer-based models are under-utilized for Siamese lightweight tracking due to the computational…
Over the past decade, there has been extensive work in developing integrated silicon photonics (SiPh) gratings for the optical addressing of trapped ion qubits in the ion trap quantum computing community. However, when viewing beam profiles…
In the manufacturing process, sensor data collected from equipment is crucial for building predictive models to manage processes and improve productivity. However, in the field, it is challenging to gather sufficient data to build robust…
Model predictive control (MPC) has established itself as the primary methodology for constrained control, enabling general-purpose robot autonomy in diverse real-world scenarios. However, for most problems of interest, MPC relies on the…
Recent advances in segmented solid-state detector arrays for rare-event searches have allowed the technology to approach the ton-scale in detector mass and the scale of meters in size. Often focused around searches for neutrinoless…
This paper presents the reconstruction and performance evaluation of the FASER$\nu$ emulsion detector, which aims to measure interactions from neutrinos produced in the forward direction of proton-proton collisions at the CERN Large Hadron…
Transformers achieve state-of-the-art performance for natural language processing tasks by pre-training on large-scale text corpora. They are extremely compute-intensive and have very high sample complexity. Memory replay is a mechanism…
A muon tracking system consisting of four 9cm x 10cm sized bulk Micromegas detectors with 128um amplification-gap and two 10cm x 10cm triple GEM detectors is foreseen for high-precision tracking of 140GeV muons at the H8 beamline at CERN…
An algorithm is presented, that provides a fast and robust reconstruction of neutrino induced upward-going muons and a discrimination of these events from downward-going atmospheric muon background in data collected by the ANTARES neutrino…
A tracking detector system has been constructed with an innovative approach to the classical multi-wire proportional chamber concept, using contemporary technologies. The detectors, covering an area of 0.58 square meters each, are optimized…
Obstacle detection and tracking represent a critical component in robot autonomous navigation. In this paper, we propose ODTFormer, a Transformer-based model to address both obstacle detection and tracking problems. For the detection task,…