One-Shot Generative Domain Adaptation in 3D GANs

One-shot Generative Domain Adaptation in 3D GANs In recent years, Generative Adversarial Networks (GANs) have achieved remarkable progress in the field of image generation. While traditional 2D generative models exhibit impressive performance across various tasks, extending this technology to 3D domains (3D-aware image generation) remains challengi...

Reliable Evaluation of Attribution Maps in CNNs: A Perturbation-Based Approach

Deep Learning Explainability Research: A Perturbation-Based Evaluation Method for Attribution Maps Background and Motivation With the remarkable success of deep learning models across various tasks, there is growing attention on the interpretability and transparency of these models. However, while these models excel in accuracy, their decision-maki...

Cross-Scale Co-Occurrence Local Binary Pattern for Image Classification

Research on Cross-Scale Co-Occurrence Local Binary Pattern (CS-COLBP) for Image Classification Image classification is a key area in computer vision, with feature extraction being its core research focus. The Local Binary Pattern (LBP), due to its efficiency and descriptive power, has been widely used in tasks such as texture classification and fac...

Warping the Residuals for Image Editing with StyleGAN

GAN Inversion and Image Editing New Method: Warping the Residuals for Image Editing with StyleGAN Background and Research Problem Generative Adversarial Networks (GANs) have made remarkable progress in the field of image generation, enabling the synthesis and editing of high-quality images. StyleGAN models, known for their semantically interpretabl...

Transformer for Object Re-Identification: A Survey

Background and Significance Object re-identification (Re-ID) is an essential task in computer vision aimed at identifying specific objects across different times and scenes. Driven by deep learning, particularly convolutional neural networks (CNNs), this field has made significant strides. However, the emergence of vision transformers has opened ne...

Teaching Research Data Management with DataLad: A Multi-Year, Multi-Domain Effort

Multi-Year, Multi-Disciplinary Efforts in Scientific Research Data Management Education Research Background With the development of modern neuroscience, Research Data Management (RDM) has become an indispensable skill for scientists. However, despite the importance of research data management for scientific research, such technical skills are often...

High-speed High-power Free-space Optical Communication via Directly Modulated Watt-class Photonic-crystal Surface-emitting Lasers

High-speed High-power Free-space Optical Communication via Directly Modulated Watt-class Photonic-crystal Surface-emitting Lasers

High-Speed High-Power Free-Space Optical Communication: Direct Modulation of Watt-Level Photonic Crystal Surface-Emitting Lasers Background Introduction As a vital light source for optical communication, semiconductor lasers are widely used due to their small size, low cost, long lifespan, and high efficiency. For example, vertical-cavity surface-e...

Hyperspectral In-Memory Computing with Optical Frequency Combs and Programmable Optical Memories

Hyperspectral In-Memory Computing and Applications of Optical Frequency Comb and Programmable Optical Memory Introduction In recent years, breakthroughs in machine learning have driven revolutionary developments in various industries, including healthcare, finance, retail, automotive, and manufacturing. These transformations have led to a surge in ...

Cell Type Mapping of Inflammatory Muscle Diseases Highlights Selective Myofiber Vulnerability in Inclusion Body Myositis

Characterization of Heterogeneity in Muscle Fiber Types and Selective Susceptibility in Inclusion Body Myositis With advancing age, the incidence of inflammatory myopathies gradually increases, among which inclusion body myositis (IBM) is the most common type, currently lacking effective treatment methods. Unlike other inflammatory myopathies, IBM ...

k-emophone: a mobile and wearable dataset with in-situ emotion, stress, and attention labels

Scientific Data Report | K-emophone: A Mobile and Wearable Dataset with On-site Emotion, Stress, and Attention Labels Background With the proliferation of low-cost mobile and wearable sensors, numerous studies have leveraged these devices to track and analyze human mental health, productivity, and behavioral patterns. However, despite the developme...