Related papers: A Brief Note of Analyzing and Plotting $\nu_\mu$ D…
With the popularity of multi-modal sensors, visible-thermal (RGB-T) object tracking is to achieve robust performance and wider application scenarios with the guidance of objects' temperature information. However, the lack of paired training…
The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the…
Object Detection is a popular field of research for recent technologies. In recent years, profound learning performance attracts the researchers to use it in many applications. Number plate (NP) detection and classification is analyzed over…
There has been an increasing interest in the monitoring of nuclear fuel for power reactors by detecting the anti-neutrinos produced during operation. Small liquid scintillator detectors have already demonstrated sensitivity to operational…
By exploiting differences in muon lifetimes it is possible to distinguish $\nu_{\mu}$ from $\bar{\nu_{\mu}}$ charged current interactions in underground neutrino detectors. Such observations would be a useful tool in understanding the…
The Taishan Antineutrino Observatory (TAO or JUNO-TAO) is a satellite experiment of Jiangmen Underground Neutrino Observatory (JUNO) and located near the Taishan nuclear power plant (NPP). TAO will measure the energy spectrum of reactor…
Object detection has long been a topic of high interest in computer vision literature. Motivated by the fact that annotating data for the multi-object tracking (MOT) problem is immensely expensive, recent studies have turned their attention…
Robust signal detection in colored noise with unknown covariance is essential in radar, cognitive radio, integrated sensing and communication (ISAC), and quantum sensing applications. This paper develops a unified analytical framework for…
Neutron scattering techniques offer a unique combination of structural and the dynamic information of atomic and molecular systems over a wide range of distances and times. The increasing complexity in science investigations driven by…
We study response selection for multi-turn conversation in retrieval-based chatbots. Existing work either concatenates utterances in context or matches a response with a highly abstract context vector finally, which may lose relationships…
Real-time emotion recognition (RTER) in conversations is significant for developing emotionally intelligent chatting machines. Without the future context in RTER, it becomes critical to build the memory bank carefully for capturing…
In this work, we present a unified model that can handle both Keyword Spotting and Word Recognition with the same network architecture. The proposed network is comprised of a non-recurrent CTC branch and a Seq2Seq branch that is further…
Recently we have proposed a new concept of a thermal neutron detector based on resistive plate chambers and 10B4C solid neutron converters, enabling to readout with high resolution in both the 3D position of neutron capture and the neutron…
Descent extensions of the soft-wall model are used to accommodate two variants of Regge trajectories of vector meson excitations. At non-zero temperatures, various options for either sequential or instantaneous disappearance of vector…
Recently, segmentation-based methods are quite popular in scene text detection, which mainly contain two steps: text kernel segmentation and expansion. However, the segmentation process only considers each pixel independently, and the…
Diagnosing and cleaning data is a crucial step for building robust machine learning systems. However, identifying problems within large-scale datasets with real-world distributions is challenging due to the presence of complex issues such…
For cloud service providers, fine-grained packet loss detection across data centers is crucial in improving their service level and increasing business income. However, the inability to obtain sufficient measurements makes it difficult…
We propose a novel analysis strategy, that leverages the unique capabilities of the DUNE experiment, to study tau neutrinos. We integrate collider physics ideas, such as jet clustering algorithms in combination with machine learning…
Shallow nitrogen-vacancy (NV) centers in diamond are promising quantum sensors but suffer from noise-induced short coherence times due to bulk and surface impurities. We present interfacial engineering via oxygen termination and graphene…
Several different experimental results are indicating the existence of anomalies in the neutrino sector. Models beyond the standard model have been developed to explain these results and involve one or more additional neutrinos that do not…