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I am now generally interested in deep learning approaches for natural language understanding.
Not only can these technologies enhance our understanding of the disease, they can also yield large imaging datasets intraoperatively that can be analyzed by deep learning approaches for more rapid and accurate pathological diagnosis.
Deep learning approaches for image retrieval achieves the best performance in recent years.
Students adopt deep learning approaches for a variety of reasons, including the perceived demand of a course and related assessments (Entwistle and Ramsden, 1983).
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This paper presents a Deep Learning approach for traffic sign recognition systems.
Arango-Argoty, G. et al. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.
In this study, we propose a deep learning approach for the efficient recognition of 3D objects with occlusion.
This paper presents a deep learning approach for the automatic classification of arterioles and venules across the entire retinal image, including vessels located at the optic disc.
Then, we present an end-to-end deep learning approach for CL, in which a network composed of fully connected layers followed by convolutional ones, performs the linear sensing and the nonlinear inference stages simultaneously.
Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors.
Our main contributions are multifold: first, to the best of our knowledge, our CRCNN framework is the first comparative deep learning approach for facial age estimation and has demonstrated its outperformance over the state-of-the-art methods by experimenting with well-known face datasets.
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