The digitization and preservation of Tamil inscriptions are crucial for safeguarding the rich cultural heritage they represent. This study presents an in-depth evaluation of deep learning-based segmentation methods sp...
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This study introduces a transformative approach to primary programming education, leveraging Augmented Reality (AR) teaching methodologies through the innovative EnvisionAR platform. In response to the dynamic technol...
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Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and ***,achieving precise segmentation remains a challenge due to various factors,in...
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Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and ***,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound *** existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,*** address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule *** MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding *** transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the *** approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the ***,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation *** results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)*** findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
In the realm of deep learning, Generative Adversarial Networks (GANs) have emerged as a topic of significant interest for their potential to enhance model performance and enable effective data augmentation. This paper...
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This study proposes a malicious code detection model DTL-MD based on deep transfer learning, which aims to improve the detection accuracy of existing methods in complex malicious code and data scarcity. In the feature...
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The agriculture industry is fundamental to the foundation of a country and is essential to the promotion of economic prosperity. It is crucial to ensure that Monitoring the health and detecting leaf infections in plan...
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As the usage of multi-cloud setups grows, resource management will become a major concern. Because of the dynamic nature of these environments, as well as fluctuating workloads and service-level targets, an effective ...
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The non-intrusive detection of Autism Spectrum Disorder (ASD) marks a significant advancement in early diagnosis and intervention. This approach allows users to upload videos to a web interface, where visual and audit...
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Face recognition is one of the most effective image-processing applications and is essential in the technological era. The identification of the facial image is a current problem for authentication purposes, particula...
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In India, annually, 67 million tonnes of food are wasted, costing the country roughly 92000 crores. The motivation behind recycling food waste is the desire to divert waste from landfills. This study aims to manage fo...
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