Terrain classification is a necessary and difficult task for all off-road robots. Most existing methods use images or proprioceptive sensors for recognition. However, while taking proprioceptive sensors as input requi...
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Recent advancements in Visual Question Answering (VQA) have been driven by the integration of complex attention mechanisms. This work introduces a novel approach aimed at enhancing multi-modal representations through ...
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Amplification-based distributed denial of service attacks (ADDoS) are a common and severe threat to the Internet. Recent reports of ADDoS attacks demonstrate that such attacks not only generate massive traffic but als...
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With the development and improvement of microfabrication equipments and process technologies, the preparation and application of the micrometer sized optical devices have become an significant field to research and op...
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Human detection is essential in areas like security surveillance, healthcare, and behavior analysis. While traditional RGB-based methods are effective, they raise significant privacy concerns by exposing personal iden...
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Named entity recognition (NER), a task that identifies and categorizes named entities such as persons or organizations from text, is traditionally framed as a multi-class classification problem. However, this approach...
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We consider the control design of stochastic discrete-time linear multi-agent systems (MASs) under a global signal temporal logic (STL) specification to be satisfied at a predefined probability. By decomposing the dyn...
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The article the efficiency of the Microgrid network when transitioning to a transactive power system that uses control algorithms called to optimize the distribution of power between sources of distributed generation ...
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In the current educational landscape, the transition towards digitalization has become crucial. However, the manual entry of data from traditional physical marksheets into digital systems remains a significant bottlen...
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In this paper, we explore the impact of conditional Deep Convolutional Generative Adversarial Networks (cDCGANs) with brain tumor image classification and introduce a new way to improve diagnosis accuracy. Shortage of...
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