Multi-organ segmentation from abdominal images is an important task. Due to the imbalance between different organ and the differences in size, shape, and contrast of different organs, it is a challenging problem in th...
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This paper presents measurements of the reflection and transmission coefficient of electromagnetic waves through concrete and two concrete-based composites: concrete with steel fibers and concrete with carbon fibers w...
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The goal of multi-object tracking(MOT) is to detect and track interested objects in videos. It is more challenging to track multiple players in soccer videos, and most existing detection and tracking approaches are no...
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An improved decoding algorithm for Reed-Solomon codes is proposed using bit flipping in combination with miscorrection detection with the help of four-level bit-marking, achieving 0.28 dB and 0.19 dB additional gains ...
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Six modulation formats referring the 400ZR standard are compared, revealing that PCS-16QAM and 4D-64PRS may offer optimal performance at different transmission distances, enhancing high-capacity optical fiber communic...
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With the rapid development of the internet, technology, and social media platforms, an increasing number of people are choosing to express their opinions on their social media accounts. This paper aims to address publ...
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Lack of awareness and experience in CPR often discourages individuals from initiating rescue actions of Out-of-hospital cardiac arrest (OHCA). This research presents a new approach to CPR training using embedded syste...
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In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh env...
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In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.
Glioblastoma is an aggressive type of brain cancer with a high mortality rate. Early and accurate glioblastoma detection is crucial for timely and effective treatment. Hyperspectral Imaging (HSI) has emerged as a prom...
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During vehicle operation, obstacles or other vehicles may require lane changes, necessitating the coordination of both lateral and longitudinal control. In predictable environments, rule-based lane-changing methods ar...
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