June 2025 - 34 articles
The prediction of anthropometric measurements from 2D body images, particularly for children, remains an under-explored area despite its potential applications in healthcare, fashion, and fitness. While pose estimation and body shape classification h...
Identifying the scriptwriter in historical manuscripts is crucial for historians, providing valuable insights into historical contexts and aiding in solving historical mysteries. This research presents a robust deep learning system designed for class...
The wavefront sensor (WFS), equipped with an electron-multiplying charge-coupled device (EMCCD) detector, is a critical component of the Cool Planets Imaging Coronagraph (CPI-C) on the Chinese Space Station Survey Telescope (CSST). Precise calibratio...
Accurate segmentation of brain vessels is critical for diagnosing cerebral stroke, yet existing AI-based methods struggle with challenges such as small vessel segmentation and class imbalance. To address this, our study proposes a novel 2D segmentati...
This study presents a unified low-parameter approach to multi-class classification of microorganisms (micrococci, diplococci, streptococci, and bacilli) based on automated machine learning. The method is designed to produce interpretable taxonomic de...
Creating grayscale images from a color reality has been an inherent human practice since ancient times, but it became a technological challenge with the advent of the first black-and-white televisions and digital image processing. Decolorization is a...
In this work, the authors compared microCT and in vivo ultrasonography in terms of accuracy and efficacy for measuring the volume of various organs in mice. Two quantification protocols were applied: ellipsoidal volume measuring maximum diameters in...
Osteoarthritis (OA) is the most prevalent degenerative joint disorder worldwide, causing significant declines in quality of life. The osteochondral junction (OCJ), a critical structural interface between deep cartilage and subchondral bone, plays an...
Objective: This study proposes a novel deep learning approach for enhancing low-dose bone scintigraphy images using an Enhanced Convolutional Autoencoder (ECAE), aiming to reduce patient radiation exposure while preserving diagnostic quality, as asse...
The synthesis of realistic fog in images is critical for applications such as autonomous navigation, augmented reality, and visual effects. Traditional methods based on Koschmieder’s law or GAN-based image translation typically assume homogeneo...
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