Aiming at the problems of small pests, blurred image, low resolution and large species difference in different growth periods of corn crops. In this paper, an accurate and efficient method for the detection of maize c...
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When using deep learning techniques to process sequential recommendation content, neural network models are typically trained relying on a wealth of historical interaction feedback. However, this feedback data often c...
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the tracking of target location plays an important role in animal behavior experiments. In order to meet the demand for high-speed transmission and fast processing of images in experiments, this paper designs an image...
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Pet owners with hectic schedules are always looking for reliable pet-sitting services to offer their furry family members the best care possible to meet their pet's basic needs. In the Philippines where pet owners...
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High-quality Magnetic Resonance Imaging (MRI) provides an aid to reliable diagnosis. By processing medical images, doctors are able to view pathological features more easily;however, since pathological features are us...
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ISBN:
(纸本)9798400708305
High-quality Magnetic Resonance Imaging (MRI) provides an aid to reliable diagnosis. By processing medical images, doctors are able to view pathological features more easily;however, since pathological features are usually small in the early stages, we would like to obtain medical images that are as clear as possible so that doctors can observe relevant features and even finer textures. therefore, applying image super-resolution technology to medical images can reconstruct high-resolution medical images without increasing hardware equipment, which helps doctors make better diagnoses of patients' conditions. the use of deep learning methods can effectively reconstruct high-resolution images. In this paper, RCAN network is applied to the medical image dataset IXI and formed a control experiment with SAN, EDSR and T2Net network, and RCAN achieves good results both in terms of data metrics and in terms of recovering images for analysis.
Medical image segmentation plays an extremely crucial role in the modern field of medicine. It is a process that involves the precise delineation and labeling of medical images through computertechnology. However, du...
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Aiming at the problems of complex fault diagnosis and slow processing speed of the current special vehicle electro-hydraulic system, this paper proposes an electro-hydraulic fault diagnosis system for special vehicle ...
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ISBN:
(纸本)9798400708305
Aiming at the problems of complex fault diagnosis and slow processing speed of the current special vehicle electro-hydraulic system, this paper proposes an electro-hydraulic fault diagnosis system for special vehicle based on RBF neural network. the improved convolutional neural network is used to extract the original data features of the special vehicle electro-hydraulic system, and then the extracted data features are sent to the RBF neural network for training, which can greatly reduce the training time, and the extracted features are in the underfitting state at this time, thereby reducing the risk of overfitting. the experimental results on the test samples show that the improved system can quickly and accurately locate the fault, and give the corresponding expert maintenance advice, which has certain reference value for the health management of special vehicles.
In the education sector, an increasing amount of research is beginning to explore the application of blockchain technology to credit banks. this paper proposes a consortium blockchain consensus mechanism tailored for ...
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Withthe booming development of modernized logistics system, smart logistics is supported by new generation of electronic informationtechnology to create a new mode of logistics business development. In this context,...
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this paper proposes an intelligent detection method based on the improved YOLOv8 algorithm for detecting lightning protection points on offshore wind turbine blades. Traditional methods rely on manual climbing and man...
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