deep learning (DL)
Study on deep learning based identification of hydrometeors observed by dual polarization Doppler weather radars
... on deep learning (DL) and fuzzy logic algorithm is proposed: firstly, the feature extraction method based on deep learning is used for training the correlation among multiple parameters and ...
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Deep Learning: A Vision for Computer
... Machine learning (ML) and deep learning ...this, deep learning is the branch of ML which outperformed the conventional techniques of machine ...and deep learning are ...
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Advanced Machine Learning Approach: Deep Learning
... of deep learning is that the two different things are not categorized by using structured / labeled ...of deep learning neural networks sends the input (image information) through entirely ...
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A deep-learning based feature hybrid framework for spatiotemporal saliency detection inside videos
... of deep learning networks, CNN is employed as it has been successfully applied in a wide range of applications including, but not limited to, handwriting digital recognition, image classification, object ...
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The potential of deep learning in marketing : insights from predicting conversion with deep learning
... by deep learning. In recent years deep learning has been at the forefront of many breakthroughs in image recognition, speech recognition and natural language ...processing. Deep ...
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Development and Evaluation of an Educational Intervention to Enhance Deep Learning and Study Skills among Pharmacy Students in Zambia
... meaningful learning, critical thinking, and problem-solving skills among pharmacy students ...their deep approach scores may not necessarily imply they were neither self-aware nor capable of adopting ...
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Detection of Mobile Keyloggers Using Deep Learning
... Shifu Hou, Lifei Chen, Yanfang Ye gave a dynamic analysis method named Component Traversal that can automatically execute the code routines of each given android app as completely as possible[3]. Based on the extracted ...
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Special Issue on Semantic Deep Learning | www.semantic-web-journal.net
... knowledge-enhanced deep learning pipeline, for example, exploring disjointness in loss functions for classification tasks [58], end-to- end memory networks [59], image-based neural user profiling [60] or ...
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A Survey Of Deep Learning Techniques For Mobile Robot Applications
... between deep learning and machine learning is that deep learning place emphasis on the subset of machine learning resources and method and uses them to solve any difficulties ...
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Accelerating the image processing by the optimization strategy for deep learning algorithm DBN
... the deep learning algorithm has high com- putational complexity and requires multiple iterations to make the parameters converge to an optimal ...the deep learning ...
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An introduction to deep learning
... In this article, we presented an introduction to deep learning; specifically described is the use of a convolutional neural network and the supervised learning process. This approach is currently ...
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Deep Learning: A Review
... using deep learning method, is facial ...unique deep learning face recognition models ...a deep convolutional neural network algorithm capable to recognize not only age and gender, but ...
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A Probability Density Function Generator Based on Deep Learning
... as activation functions in the hidden layers of the proposed deep learning model for learning actual.. 151[r] ...
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Deep Learning as a Frontier of Machine Learning: A Review
... through learning from the lower level by exploiting the hierarchical exploratory ...the deep learning methods avoid feature engineering in supervised learning ...unsupervised learning ...
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Analysing the limitations of deep learning for developmental robotics
... of deep learning has provided a significant boost to the perfor- mance of models in different areas but contain the above problems which limit its incorporation in industry in safety critical applications ...
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Machine Learning and Deep Learning Methods for Cybersecurity
... Earlier methodologies employed the use of only cybersecurity algorithms and techniques. This requires human effort to detect each and every cybersecurity threats. This includes even detection of already existing ...
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Deep learning evaluation using deep linguistic processing
... We discuss problems with the standard ap- proaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a com- plement to current practice. We demonstrate ...
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Brain Tumor Segmentation in MRI images Using Deep Learning – A Review
... the deep learning offers a very influential structure for brain image segmentation which provides considerable results compared to conventional ...for deep-learning methods is getting ...
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Research on iris image encryption based on deep learning
... years, deep learning has solved many unsolved problems in the field of artificial intelligence with its excellent fea- ture learning ability and has achieved rapid develop- ...that deep ...
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Deep Learning an Overview
... The neural network model has been previously used in Educational data mining for various purposes: predicting student's grades (Guo et al, 2014), assessment of dropout probability (Kak, Chen & Wang, 2010, p. 16; ...
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