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...

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...

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...

Use of Transcranial Oscillatory Stimulation to Reduce Cybersickness in Virtual Reality Background and Motivation Virtual Reality (VR) technology is increasingly integrated into fields such as work, healthcare, and entertainment. However, approximately 95% of VR users experience symptoms known as Cybersickness (CS), characterized by nausea, dizzines...

Deep Learning-Driven Protein Design: Generating Functional Protein Sequences Using Conditional Diffusion Models Proteins are at the core of life sciences research and applications, offering countless possibilities due to their diversity and functional complexity. With advancements in deep learning technologies, protein design has reached a new pinn...

Here’s the translation of the report, ensuring all content is preserved as requested: The research presents an enhanced MRI-based brain tumor classification method using a novel Pix2Pix Generative Adversarial Network (GAN) augmentation framework, effectively addressing challenges in data scarcity and privacy while improving diagnostic accuracy. Doe...