Results 151 to 160 of about 45,910 (264)
Insights and Considerations in Development and Performance Evaluation of Generative Adversarial Networks (GANs): What Radiologists Need to Know. [PDF]
Diagnostics (Basel)Yoon JT +4 more
europepmc +1 more source
DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu +3 more
wiley +1 more source
High Voltage, EarlyView.ABSTRACT Infrared and visible image registration is a key task in automated distribution network inspection. Previous approaches typically apply a single homography to align infrared and visible images leading to local misalignment. To address this, this study proposes a novel region‐based registration algorithm specifically designed for wide‐depth ...
Yingchen Zhang, Bo Wang, Fei Tang
wiley +1 more source
Tales of Cyberspace and Artificial Intelligence: Diverging Stakeholderships?
Global Policy, EarlyView.ABSTRACT This article traces the evolution of the Internet from the 1990s to the 2020s and compares it with the development of Artificial Intelligence (AI), particularly following the public launch of ChatGPT in late 2022. It identifies both parallels and divergencies between these two overlapping technological domains, focusing on the growing ...
Johan Eriksson, Giampiero Giacomello
wiley +1 more source
Australasian Journal of Dermatology, EarlyView.ABSTRACT Background/Objectives Convolutional neural networks (CNNs) are known, due to inherent flaws in their design, to be subject to classification error. Many of these shortcomings in classification performance were addressed in 2017 with the introduction of capsule networks (CNs).
Hayley Chai, Stephen Gilmore
wiley +1 more source
Computer Graphics Forum, EarlyView.VividHairEdit is an advanced StyleGAN2 inversion system for high‐fidelity hair transfer and editing. Our system features improved structural integration, vibrant appearance representation, and optimized latent code selection, achieving superior generation quality and usability. A user‐friendly sketch interface enables precise modifications that reflect
Eunyeong Choi, Sihun Jin, Dongjoon Kim
wiley +1 more source
Adaptive Sampling for BRDF Acquisition
Computer Graphics Forum, EarlyView.We propose a data‐driven adaptive sampling strategy that predicts the optimal sampling pattern and count for BRDF acquisition from a single image, reducing capture time while preserving quality. Abstract The bidirectional reflectance distribution function (BRDF) describes the ratio of incoming radiance to outgoing radiance for all possible pairs of ...
Behnaz Kavoosighafi +3 more
wiley +1 more source
MaX4Zero: Masked Extended Attention for Zero‐Shot Virtual Try‐On In The Wild
Computer Graphics Forum, EarlyView.Max4Zero is a zero‐shot, training‐free virtual try‐on method that leverages diffusion priors and extended attention for accurate garment transfer. By warping reference garments and mitigating texture sticking, it achieves superior fidelity, garment preservation and identity consistency over state‐of‐the‐art methods without additional training ...
Nadav Orzech +4 more
wiley +1 more source
Style Brush: Guided Style Transfer for 3D Objects
Computer Graphics Forum, EarlyView.We introduce Style Brush, a guided 3D style‐transfer method for textured meshes that provides precise creative control. It supports the use of multiple style images, smooth transitions and intuitive guidance, producing visually appealing textures that follow user intent as we demonstrate in our user study and results. Abstract We introduce Style Brush,
Áron Samuel Kovács +2 more
wiley +1 more source
Textile and colour defect detection using deep learning methods
Coloration Technology, EarlyView.Abstract Recent advances in deep learning (DL) have significantly enhanced the detection of textile and colour defects. This review focuses specifically on the application of DL‐based methods for defect detection in textile and coloration processes, with an emphasis on object detection and related computer vision (CV) tasks.
Hao Cui +2 more
wiley +1 more source