Document images serve as a medium for transmitting information;however, they are influenced by numerous environmental factors during capture, complicating the identification and processing of their content. In the dig...
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In recent years, deep learning techniques have been widely used in the field of infrared and visible image fusion (IVIF) due to their powerful feature representation. Existing methods usually use convolutional neural ...
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Although deep neural networks have demonstrated exceptional performance in various fields, especially in image processing, they still face some significant unresolved challenges. Catastrophic forgetting is one of the ...
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The AOD-Net suffers from issues such as low image quality and color distortion after defogging. An improved defogging algorithm is proposed, which applies pooling operations and dilated convolution to the convolutiona...
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This paper proposes a steel bar detection algorithm model based on the YOLOv8 object detection algorithm. It improves the network structure by using EMA (Exponential Moving Average) attention to replace the original C...
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To address the existing issues of missed detection and false detection of hard hats by mainstream detection models in complex environments, an improved hard hat detection algorithm, STOE-YOLOv5s based on YOLOv5s, has ...
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This paper investigates the ability of the search radar carried by the surface robot to detect and analyze the target and the change of the radar's performance in the complex environment, such as electromagnetic i...
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Rapid detection and response to abnormal movements of industrial robots can effectively reduce the risk of injury. Abnormal action detection requires modeling and distinguishing the complex and variable action pattern...
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Pose prediction can timely determine whether the posture of industrial robots is abnormal, thereby reducing the harm caused by abnormal actions of industrial robots. The pose prediction task requires modeling the comp...
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Adversarial attacks can generate adversarial examples by adding perturbation information to benign samples, causing neural networks to misjudge. Semantic-based adversarial attacks are a type of attack algorithm that a...
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