Factors such as public sentiment and international travel patterns can significantly influence the spread of infectious diseases. In this study, we propose a novel approach that embeds public opinion and global aviati...
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The principle of BP neural network optimized by genetic algorithm is introduced, and the methods and general steps for solving conventional problems are given. The improvement of component optimization and coding tech...
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In the wireless network environment, random backoff must be performed before packet transmission to avoid transmission collisions. Since the backoff time depends on the size of the Contention Window (CW), the setting ...
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In recent years, the neural network architecture has developed rapidly and has been widely used in the semantic segmentation of remote sensing images. In this paper, we apply the neural network to the road network ext...
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ISBN:
(数字)9789819756001
ISBN:
(纸本)9789819755998;9789819756001
In recent years, the neural network architecture has developed rapidly and has been widely used in the semantic segmentation of remote sensing images. In this paper, we apply the neural network to the road network extraction of high-resolution remote sensing images. Subsequently, a series of single-pixel coordinate points are obtained by using the refinement method. Given the different lengths of road sections, our algorithm uses a double-loop mechanism to perform multi-scale fitting of them, which improves the rough results of the neural network and enhances the accuracy of road network extraction. For multiple line segments that may be on the same road, we also propose appropriate rules to classify and merge them. Our experimental results show that compared with other methods of road network extraction, our approach can obtain better results.
This study presents a novel approach for human detection in infrared images by enhancing the RT-DETR algorithm. The aim is to overcome challenges related to low detection accuracy and real-time performance issues in i...
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With respect to enhance the teaching quality as well as training effectiveness of the sports training, Human computer Interaction (HCI) and Artificial Intelligence (AI) technologies is utilized to develop the expert s...
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An artificial intelligence (AI) system works by combining a computer program and algorithms to make a device more efficient and intelligent for tasks that are typically performed by humans. Deep learning, machine lear...
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In Industrial Internet of Things (IIoT) settings, effective data processing and energy management are essential due to the resource-limited characteristics of the linked equipment. This research introduces a unique Sa...
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The suggested method to detect the accuracy level of fake information by applying a sequence of natural language processing (NLP), blockchain, and reinforcement learning approaches. The system applies NLP algorithms t...
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Heat-resistant steel is important material for manufacture of power generation equipment. The aging grade of heat-resistant steel has an important impact on whether the equipment can operate safely. The aging grade of...
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ISBN:
(纸本)9798350386783;9798350386776
Heat-resistant steel is important material for manufacture of power generation equipment. The aging grade of heat-resistant steel has an important impact on whether the equipment can operate safely. The aging grade of heat-resistant steel needs to be judged according to metallographic images of material during on-site inspection. However, traditional manual classification method has high requirements for experience, an improved shuffle net network is proposed in this paper, which can automatically and accurately classify heat-resistant steel aging grade based on metallographic images. Due to the fact that the background of metallographic images is complex and deep image features are difficult to extract, the dual attention module is introduced into the improved network to realize accurate extraction of image feature information. In order to meet the requirements of both high accuracy and lightweight, h-swish activation function is introduced into the improved network. Metallographic images of heat-resistant steel of different aging grades are used for model training and verification. Experimental results demonstrate the feasibility and accuracy of this method, which is based on metallographic images to realize automatic classification of aging grade of heat-resistant steel.
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