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FL-W3S: Cross-domain federated learning for weakly supervised semantic segmentation of white blood cells.
Int J Med Inform
January 2025
Department of Computer Science and Artificial Intelligence, University of Udine, 33100, Italy.
Background: Segmentation models for clinical data experience severe performance degradation when trained on a single client from one domain and distributed to other clients from different domain. Federated Learning (FL) provides a solution by enabling multi-party collaborative learning without compromising the confidentiality of clients' private data.
Methods: In this paper, we propose a cross-domain FL method for Weakly Supervised Semantic Segmentation (FL-W3S) of white blood cells in microscopic images.
Generative adversarial local density-based unsupervised anomaly detection.
PLoS One
January 2025
School of Information Science and Engineering, Xinjiang University, Urumqi, China.
Anomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense, and health monitoring, as it directly affects the accuracy and security of decision-making. Existing generative adversarial nets (GANs)-based anomaly detection methods overlook the importance of local density, limiting their effectiveness in detecting anomaly objects in complex data distributions. To address this challenge, we introduce a generative adversarial local density-based anomaly detection (GALD) method, which combines the data distribution modeling capabilities of GANs with local synthetic density analysis.
View Article and Find Full Text PDFPedestrian POSE estimation using multi-branched deep learning pose net.
PLoS One
January 2025
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon.
In human activity-recognition scenarios, including head and entire body pose and orientations, recognizing the pose and direction of a pedestrian is considered a complex problem. A person may be traveling in one sideway while focusing his attention on another side. It is occasionally desirable to analyze such orientation estimates using computer-vision tools for automated analysis of pedestrian behavior and intention.
View Article and Find Full Text PDFBuffExDb: web-based tissue-specific gene expression resource for breeding and conservation programmes in Bubalus bubalis.
Database (Oxford)
January 2025
Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India.
Amidst the global challenge of extreme poverty, the livestock sector can significantly contribute to global sustainable development goals by enhancing resilience, smallholder productivity, and market participation. The Indian livestock sector is one of the largest in the world with a total livestock population of 535.82 million, ∼10.
View Article and Find Full Text PDFDeep-Learning Generated Synthetic Material Decomposition Images Based on Single-Energy CT to Differentiate Intracranial Hemorrhage and Contrast Staining Within 24 Hours After Endovascular Thrombectomy.
CNS Neurosci Ther
January 2025
Department of Radiology, Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, China.
Aims: To develop a transformer-based generative adversarial network (trans-GAN) that can generate synthetic material decomposition images from single-energy CT (SECT) for real-time detection of intracranial hemorrhage (ICH) after endovascular thrombectomy.
Materials: We retrospectively collected data from two hospitals, consisting of 237 dual-energy CT (DECT) scans, including matched iodine overlay maps, virtual noncontrast, and simulated SECT images. These scans were randomly divided into a training set (n = 190) and an internal validation set (n = 47) in a 4:1 ratio based on the proportion of ICH.
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