Due to the limitations of hardware specification of smartphones' camera system, there is still a visible gap in imaging quality between smartphones and digital singlelens reflex (DSLR) cameras. Sophisticated learn...
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image Science provides a framework for the task-based assessment of image quality. This framework has been used to support the evaluation of medical imaging system hardware, iterative reconstruction algorithms and oth...
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Effective fault detection in rotating machinery is essential for ensuring industrial systems' reliability and operational efficiency. In this work, we proposed a method for fault detection using image matching tec...
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Rendering night photography pictures is a challenging task that requires advanced processing techniques. Although deep learning-based image Signal processing (ISP) pipelines have shown promising results, current limit...
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The proceedings contain 45 papers. The special focus in this conference is on Intelligent and 3D Technologies. The topics include: Multi-scale Point Cloud Shape Completion Network Based on Deep Learning;research on Ap...
ISBN:
(纸本)9789819791279
The proceedings contain 45 papers. The special focus in this conference is on Intelligent and 3D Technologies. The topics include: Multi-scale Point Cloud Shape Completion Network Based on Deep Learning;research on Application and Effect Evaluation of Product Innovation Management Based on Deep Learning;study on Deep Learning-Based Personalised Product Recommendation Model for Autonomous Question-and-Answer Robot;application of image Watermarking Technology Based on Deep Learning in Copyright Protection;research on the Combination of Building Structural Health Monitoring and Deep Learning imageprocessing;electrical Equipment Prediction in a Variable Electromagnetic Field Using Deep Learning;state Monitoring and Fault Prediction of Wind Farm Transmission and Transformation Equipment Based on Deep Learning;application of Deep Learning algorithms in the Innovation Ecosystem of Electric Power;optimization Strategy for Inventory Management Based on Machine Learning;intelligent Design and Evaluation of Aging Adaptable Public Spaces Based on Deep Learning;performance Optimization and Acceleration of Machine Learning algorithms in Task Allocation of Mine Maintenance Robots;Application of Deep Learning to Improve the Performance of Automotive Electronic Control Unit (ECU);deep Learning-Based Scene Classification for Remote Sensing images;Improved Swarm Intelligence Optimization Algorithm Based on SL-Relu Activation Function Improvement Strategy and Its Application in Price Forecasting;Automatic Segmentation of Traumatic Penumbra in Rat Brain Based on Improved UNet++;A Brain Tumor Classification Method Based on ResNeXt-SESA Network;A LSTM Algorithm for Coastal City Cultural Scene Value Sustainable Development Forecast Improvement;pattern Recognition in Archive Analysis Using Data Mining;building Crack Detection Method Based on Convolutional Neural Network.
Cataracts are a prominent cause of blindness worldwide, yet only a small number of publications have reviewed the current state of AI research and development in this domain. Cataract surgery can be avoided in their e...
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Traditional machine learning (ML) techniques have limitations that make it difficult for existing algorithms to diagnose cervical cancer. These limitations include lower accuracy and an inability to handle complicated...
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In a computer image analysis, the main aim is to produce the image with specified appearance that provides more convenience for society and machines to detect, identify, and understand the situation. imageprocessing ...
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With the rapid development of artificial intelligence technology, deep learning has become one of the key technologies in the field of image recognition. PyTorch has become the preferred framework for researchers due ...
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ISBN:
(数字)9798350360660
ISBN:
(纸本)9798350360677
With the rapid development of artificial intelligence technology, deep learning has become one of the key technologies in the field of image recognition. PyTorch has become the preferred framework for researchers due to its flexibility, efficiency, and ease of use. This study focuses on the real-time performance of deep learning algorithms in image recognition under the PyTorch framework, and its effectiveness is verified through system experiments. The experiment revealed that the algorithm under this framework exhibits excellent real-time performance in image recognition tasks, with an average frame rate of up to 59.46 FPS and an imageprocessing delay as low as 59.44 milliseconds, fully meeting the demand for efficient processing in a wide range of application scenarios. This discovery demonstrates the powerful potential and practicality of PyTorch in the field of image recognition.
Due to the critical importance of underwater pipeline integrity, particularly in the oil and gas transportation sector. This paper addresses the significance of applying low-rank matrix and sparse representation theor...
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