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Optimizing VGG16 deep learning model with enhanced hunger games search for logo classification.
Sci Rep
December 2024
Department of Computer Science, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming.
View Article and Find Full Text PDFA multi-modal geospatial-temporal LSTM based deep learning framework for predictive modeling of urban mobility patterns.
Sci Rep
December 2024
Department of Computing and Information Systems, Sunway University, 47500, Petaling Jaya, Selangor Darul Ehsan, Malaysia.
Urban mobility prediction is crucial for optimizing resource allocation, managing transportation systems, and planning urban development. We propose a novel framework, GeoTemporal LSTM (GT-LSTM), designed to address the intricate spatiotemporal dynamics of urban environments. GT-LSTM integrates temporal dependencies with geographic information through a multi-modal approach that combines attention mechanisms and Recurrent Neural Networks (RNNs).
View Article and Find Full Text PDFDiagnostic criteria for temporomandibular joint osteoarthritis using standardized uptake value in single-photon emission computed tomography-computed tomography.
Sci Rep
December 2024
Department of Oral and Maxillofacial Surgery, Yonsei University College of Dentistry, Gangnam Severance Hospital, 211 Eonju-ro, Gangnam-gu, Seoul, 06273, Republic of Korea.
This study aimed to investigate the cutoff values of standardized uptake values (SUVs) and their accuracy using single-photon emission computed tomography-computed tomography (SPECT-CT) for temporomandibular joint (TMJ) osteoarthritis (OA) based on magnetic resonance imaging (MRI) and clinical examination. We included 106 joints of 53 patients with TMJ OA. SUVmax and SUVpeak of each TMJ was measured.
View Article and Find Full Text PDFSelecting the optimal candidates for percutaneous mitral valvuloplasty using multi-modality imaging.
Eur Heart J Cardiovasc Imaging
December 2024
Division of Radiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea.
Aims: This study compared echocardiography (echo) and cardiac computed tomography (CT) in measuring the Wilkins score and evaluated the potential added benefit of CT in predicting immediate percutaneous mitral valvuloplasty (PMV) outcomes in rheumatic mitral stenosis (MS) patients deemed eligible for PMV by echo.
Methods And Results: From a multicentre registry of 3,140 patients with at least moderate MS, we included 96 patients (age 56.4±11.
Successful Multi-Modal Laser Intervention and Histopathological Evaluation of Multiple Glomangiomas.
Lasers Surg Med
December 2024
Department of Dermatology, Veterans Health Administration, San Antonio, Texas, USA.
Objectives: Glomangiomas are benign vascular malformations that exist within the spectrum of glomuvenous malformations which consist of varying amounts of glomus cells, vascular spaces, and smooth muscle. Glomangiomas are often treated due to associated pain, particularly when located on pressure areas such as the back or extensor surfaces, which can cause difficulty with certain activities and occupational functions. Histologically glomangiomas consist of prominent dilated vascular spaces lined by glomus cells typically situated in the deep-dermis to subcutaneous fat which limits treatment to modalities capable of reaching the depth of the tumor including excision, sclerotherapy, and laser therapy.
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