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Yifan Liu, Weiliang Gao, Tingting Zhao, Zhiyong Wang and Zhihua Wang
The aim of this study is to enhance the efficiency and lower the expense of detecting cracks in large-scale concrete structures. A rapid crack detection method based on deep learning is proposed. A large number of artificial samples from existing concret...
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Kyungho Yu, Hyoungju Kim, Jeongin Kim, Chanjun Chun and Pankoo Kim
Text-to-image technology enables computers to create images from text by simulating the human process of forming mental images. GAN-based text-to-image technology involves extracting features from input text; subsequently, they are combined with noise an...
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Rong Zhen, Yingdong Ye, Xinqiang Chen and Liangkun Xu
Aiming at the problem of high-precision detection of AtoN (Aids to Navigation, AtoN) in the complex inland river environment, in the absence of sufficient AtoN image types to train classifiers, this paper proposes an automatic AtoN detection algorithm Ai...
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Sai Sambasiva Rao Bairaboina and Srinivasa Rao Battula
White blood cells (WBCs) must be evaluated to determine how well the human immune system performs. Abnormal WBC counts may indicate malignancy, tuberculosis, severe anemia, cancer, and other serious diseases. To get an early diagnosis and to check if WBC...
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Sirine Ammar, Thierry Bouwmans and Mahmoud Neji
Recently, Deep Neural Networks (DNNs) have become a central subject of discussion in computer vision for a broad range of applications, including image classification and face recognition. Compared to existing conventional machine learning methods, deep ...
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Hong-Chan Chang, Yi-Che Wang, Yu-Yang Shih and Cheng-Chien Kuo
A homemade defective model of an induction motor was created by the laboratory team to acquire the vibration acceleration signals of five operating states of an induction motor under different loads. Two major learning models, namely a deep convolutional...
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Shucong Liu, Hongjun Wang and Xiang Zhang
In gas turbine rotor systems, an intelligent data-driven fault diagnosis method is an important means to monitor the health status of the gas turbine, and it is necessary to obtain sufficient fault data to train the intelligent diagnosis model. In the ac...
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Yan Zhang, Shiyun Wa, Pengshuo Sun and Yaojun Wang
To address the current situation, in which pear defect detection is still based on a workforce with low efficiency, we propose the use of the CNN model to detect pear defects. Since it is challenging to obtain defect images in the implementation process,...
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Sagar Kora Venu and Sridhar Ravula
Medical image datasets are usually imbalanced due to the high costs of obtaining the data and time-consuming annotations. Training a deep neural network model on such datasets to accurately classify the medical condition does not yield the desired result...
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Pilar Rosado, Rubén Fernández and Ferran Reverter
Generative adversarial networks (GANs) provide powerful architectures for deep generative learning. GANs have enabled us to achieve an unprecedented degree of realism in the creation of synthetic images of human faces, landscapes, and buildings, among ot...
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