Related papers: Neural Networks for 3D Characterisation of AGATA C…
The unprecedented capabilities of state-of-the-art segmented germanium-detector arrays, such as AGATA and GRETA, derive from the possibility of performing pulse-shape analysis. The comparison of the net- and transient-charge signals with…
The next generation of radioactive ion beam facilities, which will give experimental access to many exotic nuclei, are presently being developed. At the same time the next generation of high resolution gamma-ray spectrometers, based on…
The Advanced GAmma Tracking Array (AGATA) is a European project to develop and operate the next generation gamma-ray spectrometer. AGATA is based on the technique of gamma-ray energy tracking in electrically segmented high-purity germanium…
AGATA is a modern $\gamma$-ray spectrometer for in-beam nuclear structure studies, based on $\gamma$-ray tracking. Since more than a decade, it has been operated performing experimental physics campaigns in different international…
Graph-based learning excels at capturing interaction patterns in diverse domains like recommendation, fraud detection, and particle physics. However, its performance often degrades under distribution shifts, especially those altering…
The Phase-Space approach (PSA), which was originally introduced in [Lacroix et al., Phys. Rev. D 106, 123006 (2022)] to describe neutrino flavor oscillations for interacting neutrinos emitted from stellar objects is extended to describe…
We present an experimental demonstration of Additive Point Source Localization (APSL), a sparse parametric imaging algorithm that reconstructs the 3D positions and activities of multiple gamma-ray point sources. Using a handheld gamma-ray…
In pulsar astronomy, detecting effective pulsar signals among numerous pulsar candidates is an important research topic. Starting from space X-ray pulsar signals, the two-dimensional autocorrelation profile map (2D-APM) feature modelling…
This paper proposes a pose-graph attentional graph neural network, called P-GAT, which compares (key)nodes between sequential and non-sequential sub-graphs for place recognition tasks as opposed to a common frame-to-frame retrieval problem…
Particle-based shape modeling (PSM) is a popular approach to automatically quantify shape variability in populations of anatomies. The PSM family of methods employs optimization to automatically populate a dense set of corresponding…
The performance of the Advanced GAmma Tracking Array (AGATA) at GANIL is discussed, on the basis of the analysis of source and in-beam data taken with up to 30 segmented crystals. Data processing is described in detail. The performance of…
An essential metric for the quality of a particle-identification experiment is its statistical power to discriminate between signal and background. Pulse shape discrimination (PSD) is a basic method for this purpose in many nuclear,…
Action coordination in human structure is indispensable for the spatial constraints of 2D joints to recover 3D pose. Usually, action coordination is represented as a long-range dependence among body parts. However, there are two main…
Aspect based sentiment analysis (ABSA) can provide more detailed information than general sentiment analysis, because it aims to predict the sentiment polarities of the given aspects or entities in text. We summarize previous approaches…
$\gamma$-ray spectroscopy of fission fragments is a powerful method for studies of nuclear structure properties. Recent results on the spectroscopy of fission fragments, using the combination of the AGATA $\gamma$-ray tracking array and the…
Gait recognition is one of the most promising video-based biometric technologies. The edge of silhouettes and motion are the most informative feature and previous studies have explored them separately and achieved notable results. However,…
The state-of-the-art solutions for Aspect-Level Sentiment Analysis (ALSA) were built on a variety of deep neural networks (DNN), whose efficacy depends on large amounts of accurately labeled training data. Unfortunately, high-quality…
The Long Short-Term Memory (LSTM) neural network based data association algorithm named as DeepDA for multi-target tracking in clutters is proposed to deal with the NP-hard combinatorial optimization problem in this paper. Different from…
We propose selective-training Gaussian head avatars (STGA) to enhance the details of dynamic head Gaussian. The dynamic head Gaussian model is trained based on the FLAME parameterized model. Each Gaussian splat is embedded within the FLAME…
A novel method based on pulse area analysis(PAA) was presented for acquisition nuclear spectrum by the digitizer. PAA method can be used as a substitute for the traditional method of pulse height analysis (PHA). In the PAA method a…