Vehicular Ad-Hoc Networks (VANETs) have emerged as a captivating field of research due to the escalating number of vehicles on the road in recent years. Ensuring a secure Intelligent Transportation System (ITS) is imp...
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Lunar domes have always been one of the important windows to understand lunar volcanic activities, but traditional geological dome identification methods are costly. This study attempts to establish an automatic ident...
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Generally, depression is the most prevalent mental disorder, which has affected hundreds of people around the world and causes a high risk of committing suicide. Automatic diagnosis of depression detection plays a vit...
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Pneumonia has been a concerning issue worldwide. This infectious disease has a higher mortality rate than Covid-19. More than two million individuals lost their lives in 2019 out of which almost 600,000 were infants l...
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The shipping industry has irreplaceable importance in international trade and commerce. How to dynamically price different containers has long been a hot topic due to its direct connection to the final revenue. Two cr...
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This study aims at exploring the use of internet of things technology and data analytics in the field of supply chain management. Using a range of software tools, including Apache Kafka, Apache NiFi, Python libraries ...
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This study proposes a multi-modal fusion framework Multitrans based on the Transformer architecture and self-attention mechanism. This architecture combines the study of non-contrast computed tomography (NCCT) images ...
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Image semantic segmentation is an important branch of computer vision of a wide variety of practical applications such as medical image analysis,autonomous driving,virtual or augmented reality,*** recent years,due to ...
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Image semantic segmentation is an important branch of computer vision of a wide variety of practical applications such as medical image analysis,autonomous driving,virtual or augmented reality,*** recent years,due to the remarkable performance of transformer and multilayer perceptron(MLP)in computer vision,which is equivalent to convolutional neural network(CNN),there has been a substantial amount of image semantic segmentation works aimed at developing different types of deep learning *** survey aims to provide a comprehensive overview of deep learning methods in the field of general image semantic ***,the commonly used image segmentation datasets are ***,extensive pioneering works are deeply studied from multiple perspectives(e.g.,network structures,feature fusion methods,attention mechanisms),and are divided into four categories according to different network architectures:CNN-based architectures,transformer-based architectures,MLP-based architectures,and ***,this paper presents some common evaluation metrics and compares the respective advantages and limitations of popular techniques both in terms of architectural design and their experimental value on the most widely used ***,possible future research directions and challenges are discussed for the reference of other researchers.
This study investigates the impact of various feature enhancement methods on the accuracy of a deep learning model used for the classification of wild animal. We specifically compare three attention-based mechanisms, ...
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Image deep features extracted by pre-trained networks are known to contain rich and informative representations. In this paper, we present Deep Degradation Response (DDR), a method to quantify changes in image deep fe...
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