The implementation of smart fertigation systems in the agriculture industry is highly encouraged by the Malaysian government. Traditional manual monitoring and optimization approaches have proven unsatisfactory since ...
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Tuberculosis (TB) remains a significant global public health concern as a highly infectious disease. One of the most effective ways of diagnosing TB is through chest X-ray (CXR) imaging. However, accurately segmenting...
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ISBN:
(数字)9783031523885
ISBN:
(纸本)9783031523878
Tuberculosis (TB) remains a significant global public health concern as a highly infectious disease. One of the most effective ways of diagnosing TB is through chest X-ray (CXR) imaging. However, accurately segmenting lungs in CXR images is challenging due to image variations and disease complexity. Manually annotating many CXR images is a time-consuming and expensive process. This has led to a scarcity of labeled data, making it difficult to train accurate deep learning models for lung segmentation. To address these challenges, we propose a novel approach to automate the segmentation of lungs in CXR images. First, we trained a variational autoencoder (VAE) on an unlabeled dataset to learn the important features and extract the reconstructed images. This allowed us to capture underlying patterns and structures in the data. In the second step, we used the U-Net model for segmentation, which takes the original images along with the reconstructed images generated by the VAE to guide the segmentation process. In the other hand, Active Learning (AL) is used to select the most informative samples for annotation by using a two-step query method that involves calculating sample complexity and potential value. Sample complexity was calculated using a fusion of multiple estimate models, which allowed us to estimate the amount of data needed to achieve a certain level of performance. Potential value was defined as the activation value of a sample and was used to guide the interactive query process. Experimental results demonstrated that our method achieved an average Dice score of 95% and an Intersection over Union (IoU) of 92% on the testing set, indicating a high level of accuracy in lung segmentation, while minimizing the number of labeled examples needed to just 10% of the dataset. Our approach obtains state-of-the-art performance on two public CXR datasets. Overall, our proposed method is a promising approach for improving the accuracy and efficiency of lung segmentation
Convolutional Neural networks (CNNs) are powerful tools for image classification when performed on the same dataset. However, when trying to use the trained CNN to classify images on unseen datasets, the performa...
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The paper considers the development of a methodology for constructing complex algorithms based on the interval representation of intuitionistic fuzzy sets in accordance with the type of problem posed. Algorithms for a...
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Natural Language Processing is one of the useful tools in the field of Knowledge Management. Sentiment analysis is an associated application area of such field to determine people’s thoughts on any topic. These opini...
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When designing a new better product, besides all the engineering knowledge, time and money, more modern techniques as possible should be presented at any stage of the development process. Hence, "brainstorming&qu...
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In the banking sector, predicting loan acceptance is a crucial task, and machine learning techniques may be used to create models that can do this. To identify which machine learning method produces the best results f...
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We presents a comprehensive approach for refactoring healthcare systems using natural language processing (NLP), Command Query Responsibility Segregation (CQRS), and Gang of four (GoF) design patterns. The proposed me...
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Iron ore is a crucial raw material for the production of steel, but its quality is dependent on the presence of impurities. In this study, we aimed to estimate the impurities present in an iron ore sample and assess t...
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Additive manufacturing (AM) is recognized as a valuable method for producing functional parts in many global industries. It has been increasingly applied even in military manufacturing companies due to its specific ch...
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