Searcharxiv⌕ Search

arXiv subjects

Bian Yang

Publications and source records attributed to Bian Yang.

8 recordsLinked to original sources
arXiv2026

Doppler-shifted X-ray Spectroscopy of Nonradiative Electron Capture in Relativistic Collisions of Xe54+ Ions with Kr and Xe Atoms

We present an angular-resolved Doppler spectroscopy study of nonradiative electron capture in relativistic collisions of bare Xe54+ ions with Kr and Xe gas targets at the HIRFL-CSR storage ring. The energy spectra and angular distributions of X-rays emitted from fast-moving down-charged projectiles were measured at five observation angles of 35{\deg}, 60{\deg}, 90{\deg}, 120{\deg}, and 145{\deg} and three collision energies of 95, 146, and 197 MeV/u by employing the effect of Doppler shift. The transition intensities of Xe53+ ions with small energy differences were precisely determined. In symmetric Xe54+ \to Xe collisions, the transition intensities of Xe53+ and Xe52+ ions were identified when X-rays emitted by projectiles overlapped with K X-rays arising from target ionization. The anisotropy parameters of the K{\alpha_1}(+M2) transition were derived from the angular emission patterns of the corresponding spectral lines. The relative populations of the L, M, and N-shell excited levels of Xe53+ and Xe52+ were further deduced from the intensity ratios of I(Ly-{\beta})/I(Ly-{\alpha}), I(Ly-{\gamma})/I(Ly-{\alpha}), and I(K{\alpha})/I(Ly-{\alpha}). The energy dependence of the population of excited projectile levels was obtained for both targets. Furthermore, the experimental results were compared with theoretical calculations of nonradiative single- and double-electron capture based on the relativistic eikonal approximation and the independent-electron approximation. These findings provide valuable insights into the magnetic-sublevel population and n-resolved state-selective population of excited states produced in relativistic collisions of highly charged heavy ions with multi-electron atoms.

physics.atom-ph↗
arXiv2026

Angular distribution of K{\alpha} x rays following nonradiative double electron capture in relativistic collisions of Xe54+ ions with Kr and Xe atoms

We present experimental study of nonradiative double electron capture processes in collisions of 95 and 146 MeV/u bare xenon ions with krypton and xenon gaseous atoms at the HIRFL-CSR storage ring. Angular distributions of the characteristic K{\alpha} radiation of the down-charged projectile ions Xe52+* are measured, which are closely related to the magnetic sublevel population of the excited 1s2l_j states of Xe52+*. It was found that the K{\alpha}1 radiation shows pronounced anisotropic and is sensitive to the collision energies and the target atoms, whereas the K{\alpha}2 radiation gives rise to isotropic. Moreover, obviously difference in the anisotropy parameters of Lyman-{\alpha}1 of Xe53+* ions and K{\alpha} transitions of Xe52+* ions separately following nonradiative single and double electron capture into the L-shell levels of projectiles is obtained and discussed.

physics.atom-ph↗
arXiv2024

The Impact of Generalization Techniques on the Interplay Among Privacy, Utility, and Fairness in Image Classification

This study investigates the trade-offs between fairness, privacy, and utility in image classification using machine learning (ML). Recent research suggests that generalization techniques can improve the balance between privacy and utility. One focus of this work is sharpness-aware training (SAT) and its integration with differential privacy (DP-SAT) to further improve this balance. Additionally, we examine fairness in both private and non-private learning models trained on datasets with synthetic and real-world biases. We also measure the privacy risks involved in these scenarios by performing membership inference attacks (MIAs) and explore the consequences of eliminating high-privacy risk samples, termed outliers. Moreover, we introduce a new metric, named \emph{harmonic score}, which combines accuracy, privacy, and fairness into a single measure. Through empirical analysis using generalization techniques, we achieve an accuracy of 81.11\% under $(8, 10^{-5})$-DP on CIFAR-10, surpassing the 79.5\% reported by De et al. (2022). Moreover, our experiments show that memorization of training samples can begin before the overfitting point, and generalization techniques do not guarantee the prevention of this memorization. Our analysis of synthetic biases shows that generalization techniques can amplify model bias in both private and non-private models. Additionally, our results indicate that increased bias in training data leads to reduced accuracy, greater vulnerability to privacy attacks, and higher model bias. We validate these findings with the CelebA dataset, demonstrating that similar trends persist with real-world attribute imbalances. Finally, our experiments show that removing outlier data decreases accuracy and further amplifies model bias.

cs.LG↗
arXiv2024

E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent Space

Face inpainting, the technique of restoring missing or damaged regions in facial images, is pivotal for applications like face recognition in occluded scenarios and image analysis with poor-quality captures. This process not only needs to produce realistic visuals but also preserve individual identity characteristics. The aim of this paper is to inpaint a face given periocular region (eyes-to-face) through a proposed new Generative Adversarial Network (GAN)-based model called Eyes-to-Face Network (E2F-Net). The proposed approach extracts identity and non-identity features from the periocular region using two dedicated encoders have been used. The extracted features are then mapped to the latent space of a pre-trained StyleGAN generator to benefit from its state-of-the-art performance and its rich, diverse and expressive latent space without any additional training. We further improve the StyleGAN output to find the optimal code in the latent space using a new optimization for GAN inversion technique. Our E2F-Net requires a minimum training process reducing the computational complexity as a secondary benefit. Through extensive experiments, we show that our method successfully reconstructs the whole face with high quality, surpassing current techniques, despite significantly less training and supervision efforts. We have generated seven eyes-to-face datasets based on well-known public face datasets for training and verifying our proposed methods. The code and datasets are publicly available.

cs.CV↗
arXiv2024

ChatGPT and biometrics: an assessment of face recognition, gender detection, and age estimation capabilities

This paper explores the application of large language models (LLMs), like ChatGPT, for biometric tasks. We specifically examine the capabilities of ChatGPT in performing biometric-related tasks, with an emphasis on face recognition, gender detection, and age estimation. Since biometrics are considered as sensitive information, ChatGPT avoids answering direct prompts, and thus we crafted a prompting strategy to bypass its safeguard and evaluate the capabilities for biometrics tasks. Our study reveals that ChatGPT recognizes facial identities and differentiates between two facial images with considerable accuracy. Additionally, experimental results demonstrate remarkable performance in gender detection and reasonable accuracy for the age estimation tasks. Our findings shed light on the promising potentials in the application of LLMs and foundation models for biometrics.

cs.CV↗
arXiv2023

EFaR 2023: Efficient Face Recognition Competition

This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size. The evaluation of submissions is extended to bias, cross-quality, and large-scale recognition benchmarks. Overall, the paper gives an overview of the achieved performance values of the submitted solutions as well as a diverse set of baselines. The submitted solutions use small, efficient network architectures to reduce the computational cost, some solutions apply model quantization. An outlook on possible techniques that are underrepresented in current solutions is given as well.

cs.CV↗
arXiv2017

Production and decay of K-shell hollow krypton in collisions with 52 - 197 MeV/u bare xenon ions

X-ray spectra of K-shell hollow krypton atoms produced in single collisions with 52 - 197 MeV/u Xe54+ ions are measured in a heavy-ion storage ring equipped with an internal gas-jet target. Energy shifts of the Kα_1,2^s, Kα_1,2^(h,s), and K\b{eta}_1,3^s transitions are obtained. Thus, the average number of the spectator L-vacancies presented during the x-ray emission is deduced. From the relative intensities of the Kα_1,2^s and Kα_1,2^(h,s) transitions, the ratio of K-shell hollow krypton to singly K-shell ionized atoms is determined to be 14 - 24%. In the considered collisions, the K-vacancies are mainly created by the direct ionization which cannot be calculated within the perturbation descriptions. The experimental results are compared with a relativistic coupled channel calculation performed within the independent particle approximation.

physics.atom-ph↗