In today's computing era, fog computing has emerged as a transformative paradigm, facilitating real-time data processing at the network edge to reduce latency and enhance responsiveness. However, ensuring optimal ...
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Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,...
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Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.
Lung cancer is a specific kind of malignancy that arises in the tissues of the lungs, specifically in the cells that comprise the lining of the respiratory passages. Smoking is well recognized as the primary etiologic...
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Real-world advanced robotics applications cannot be con¬ceived without the employment of onboard visual perception. By per¬ception we refer not only to image acquisition, but more importantly to the informat...
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Recently, many patients have sought treatment ideas through social media. The medical texts include a wealth of information, including a huge number of medical musculatures and symptoms. Developing an intelligence mod...
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We demonstrated a MOSCAP silicon microring modulator integrated with high-mobility titanium-doped indium oxide, achieving sub-volt 0.8 Vpp modulation up to 25 Gb/s, marking a milestone in transparent conducting oxide ...
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Smart fish monitoring system using IoT used to maintain a fresh water in the aquarium for aqua life environment. It features to monitor the freshness of the water for healthier aqua life environment. This proposed sys...
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The surge of social media highlights the necessity for sophisticated instruments to assess public sentiment toward individuals and entities. Present approaches often fall short in capturing the multifaceted nature of ...
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This study aims to improve the performance of organic to recyclable waste through deep learning techniques. Negative impacts on environmental and Social development have been observed relating to the poor waste segreg...
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Networks form an integral part of our daily lives, comprising structures known as nodes connected via ties. These networks exhibit a complex interplay of random and structured features. We encounter networks regularly...
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Networks form an integral part of our daily lives, comprising structures known as nodes connected via ties. These networks exhibit a complex interplay of random and structured features. We encounter networks regularly in our daily activities, whether it is logging into websites, commuting by train, going to work, or attending school. Networks are prevalent in various academic disciplines and practical applications, spanning biology, physics, engineering, social science, and numerous other fields. The early 21st century has witnessed a rapid expansion of techniques facilitating human interaction, significantly impacting behavior and social bonding in both urban and rural settings. The availability and accessibility of extensive population datasets have spurred ongoing research into understanding and shaping human inclinations and sociological phenomena in unconventional ways. This review delves into the nuanced aspects of social physics, exploring the rationale behind choosing this research topic, various conceptual frameworks, categorizations, and distinctions between machine learning and deep learning. The article briefly outlines the advantages of leveraging big data in social physics, highlighting its transformative potential. Lastly, the authors provide insights into several applications of social physics in subsequent sections, offering a glimpse into its real-world implications.
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