A complex endocrine disorder that affects fertile women, polycystic ovary syndrome, also known as PCOS, is characterized by an extensive spectrum of symptoms. This work extends previous efforts in PCOS detection and t...
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We introduce a novel BiMoeFormer based on the Transformer architecture for 3D human motion prediction. Previous approaches primarily focus on the relationships between body joints in human poses, while neglecting thei...
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Recent advancements in Vision-Language Pre-training (VLP) techniques have greatly improved performance in Scene Text Detection tasks by leveraging the rich visual and textual content in scene text images. We propose a...
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In the current global context, people face the risk of losing their lives to various fatal diseases. One significant concern is the potential impact of cellular network radiation and mobile phone usage on health, part...
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Using color fundus imaging to identify diabetic retinopathy (DR) is a tough process that requires skilled doctors to comprehend the existence and significance of certain small characteristics. This effort is further c...
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The Psychological and neurobiological phenomenon is called an emotion. Nowadays, using emotional engineering for the prediction of human emotions is one of the major attempts of Machine Learning (ML). However, the cap...
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Current diagnostic procedures, such as imaging tests and biopsies, are time intensive and prone to human error. As a result, we employed deep learning to uncover patterns and identify lung cancer from histology pictur...
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Credit card fraud detection is an increasingly critical issue due to the growth of digital transactions and the sophistication of fraudulent activities. This study proposes a hybrid framework combining Graph Neural Ne...
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Detecting out-of-distribution (OOD) data is crucial for the safe and reliable deployment of deep learning models in open-world scenarios. While energy-based models (EBMs) have shown promising potential in OOD detectio...
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Traditional survey systems struggle with data immutability, privacy protection, and reliable storage. These limitations compromise transparency, security, and data integrity. This paper proposes a decentralized and se...
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