Deep learning techniques are widely used in the field of medicine and image classification. In past studies, SwimTransformer and RepVGG are very efficient and classical deep learning models. Multi-scale feature fusion and attention mechanisms are eff...
A zero-day vulnerability is a critical security weakness of software or hardware that has not yet been found and, for that reason, neither the vendor nor the users are informed about it. These vulnerabilities may be taken advantage of by malicious pe...
Accurate monthly runoff forecasting is vital for water management, flood control, hydropower, and irrigation. In glacierized catchments affected by climate change, runoff is influenced by complex hydrological processes, making precise forecasting eve...
The growing reliance on video conferencing software brings significant benefits but also introduces challenges, particularly in managing audio quality. In multi-participant settings, ambient noise and interruptions can hinder speaker recognition and ...
As the fashion e-commerce markets rapidly develop, tens of thousands of products are registered daily on e-commerce platforms. Individual sellers register products after setting up a product category directly on a fashion e-commerce platform. However...
In recent decades, automatic train operation (ATO) systems have been gradually adopted by many metro systems, primarily due to their cost-effectiveness and practicality. However, a critical examination reveals computational constraints, adaptability ...
To investigate the potential of artificial intelligence (AI) in Cervical Vertebral Maturation (CVM) staging, we developed and compared AI-based qualitative CVM and AI-based quantitative QCVM methods. A dataset of 3,600 lateral cephalometric images fr...
The rapid growth of Android applications has led to an increase in security threats, while traditional detection methods struggle to combat advanced malware, such as polymorphic and metamorphic variants. To address these challenges, this study introd...
Surveillance systems are integral to ensuring public safety by detecting unusual incidents, yet existing methods often struggle with accuracy and robustness. This study introduces an advanced framework for anomaly recognition in surveillance, leverag...
The adoption of deep learning in ECG diagnosis is often hindered by the scarcity of large, well-labeled datasets in real-world scenarios, leading to the use of transfer learning to leverage features learned from larger datasets. Yet the prevailing as...
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