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Recent Advances in Deep Learning Techniques and Its Applications: An Overview

springer

Cited 15|Views0
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Abstract
Learning with images and their classification, segmentation, localization, annotation, and abnormally detection is one of the current challenging and exciting task for the researchers. Recently deep learning techniques give excellent performance in Object Detection, Speech Recognition, Abnormality Detection, Business Analysis, and almost all other domains. But one important implication of deep learning techniques can found in Medical Image Analysis. Deep learning techniques beat the human-level performance and come with a better solution in the medical domain. Among different deep learning techniques Convolutional Neural Network, Recurrent Neural Network, Long Short-Term Memory, Deep Belief Network models are topmost priority for the researchers. In this paper, we briefly examine different application area of deep learning techniques and some current state-of-the-art performances of it. Moreover, we also discuss some of the limitations of Deep Learning techniques. As expected this paper creates a clear understanding of Deep Learning techniques and its applications.
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Key words
Deep learning, CNN, RNN, Health care
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