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applications of deep learning

Applications, Promises, and Pitfalls of Deep Learning for Fluorescence Image Reconstruction

Applications, Promises, and Pitfalls of Deep Learning for Fluorescence Image Reconstruction

... consistency. Applications of Deep Learning to mi- croscopy typically fail to capture temporal patterns: predictions are made independently, ...

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Deep Learning Applications in Business Activities

Deep Learning Applications in Business Activities

... abilities, deep learning method have great potential applications in wider business ...companies, deep learning method has achieved great success in the aspect of reducing expense of ...

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A Survey Of Deep Learning Techniques For Mobile Robot Applications

A Survey Of Deep Learning Techniques For Mobile Robot Applications

... many applications of considerable community and financial ...used deep learning to classify terrain and solve any exploration shortcomings by generating control commands for its human operator so as ...

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A SURVEY ON AUGMENTED REALITY APPLICATIONS USING DEEP LEARNING

A SURVEY ON AUGMENTED REALITY APPLICATIONS USING DEEP LEARNING

... study, deep learning and AR issues are explained, and the research results of the combination of the two are ...of deep learning. The use of deep learning in important issues ...

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Deep learning for healthcare applications based on physiological signals: A review

Deep learning for healthcare applications based on physiological signals: A review

... that deep learning algorithms performs well with large and diverse datasets which has two ...that deep learning algorithms will perform well in practical settings, because clinical routine ...

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Deep learning applications and challenges in big data analytics

Deep learning applications and challenges in big data analytics

... a Deep Learning algorithm can be used for incremental feature learning on very large datasets, employing denoising autoencoders ...purposes. Deep Learning algorithms in general use ...

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Deep learning for smart agriculture: Concepts, tools, applications, and opportunities

Deep learning for smart agriculture: Concepts, tools, applications, and opportunities

... years, Deep Learning (DL), such as the algorithms of Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Generative Adversarial Networks (GAN), has been widely studied and applied in ...

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Exploring End-to-end Deep Learning Applications for Event Classification at CMS

Exploring End-to-end Deep Learning Applications for Event Classification at CMS

... machine learning techniques accomplish this using traditional hand-engineered features like particle 4-momenta, motivated by our understanding of particle decay phe- ...powerful deep learning ...

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Deep Learning Applications in the Medical Image Recognition

Deep Learning Applications in the Medical Image Recognition

... the deep learning systems and its major applications in various ...the learning process of human brain, which accumulate experiences from thousands of ...Besides, learning by ...

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Review on: Deep Learning and Applications

Review on: Deep Learning and Applications

... Network, Deep Learning and Decision Tree Learning are just piece of the ...days applications in various ...profound learning research through barlications over the ongoing years in ...

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Convolutional Neural Networks vs  Convolution Kernels: Feature Engineering for Answer Sentence Reranking

Convolutional Neural Networks vs Convolution Kernels: Feature Engineering for Answer Sentence Reranking

... Considering recent applications of deep learning models to the problem of matching sentences, our network is most similar to the models in (Hu et al., 2014) applied for computing sentence similarity ...

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E534 Big Data Applications and Analytics Class (Deep Learning version) Lectures

E534 Big Data Applications and Analytics Class (Deep Learning version) Lectures

... Data Applications and Analytics Sports Informatics Part I (Unit 32) Section Summary (Parts I, II, III): Sports sees significant growth in analytics with pervasive statistics shifting to more sophisticated ...

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A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends

A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends

... to the competing methods. Dedinec et al. [173] employed a Deep Belief Network (DBN) for short term load forecasting of the Former Yugoslavian Republic of Macedonia. The proposed network comprised several stacks ...

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Captioning for Motion Detection for video surveillance Applications using Deep Learning

Captioning for Motion Detection for video surveillance Applications using Deep Learning

... together form the M-RNN. They have tested the model on IAPR TC-12, Flickr 8K, Flickr 30K and MS COCO datasets. It has significant performance improvement over the others. In [8] they have proposed a new model which ...

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A SURVEY ON DEEP LEARNING TECHNIQUES, APPLICATIONS AND CHALLENGES

A SURVEY ON DEEP LEARNING TECHNIQUES, APPLICATIONS AND CHALLENGES

... Deep learning is an emerging research area in machine learning and pattern recognition ...field. Deep learning refers to machine learning techniques that use supervised or ...

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Natural Language Processing Applications in Deep Learning Methods

Natural Language Processing Applications in Deep Learning Methods

... of learning methods like the perceptron model and therefore the Hebb Rule have been used in the past, such corrections are typically created in modern networks using random gradient descent, considering the ...

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Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

... Cruz et al [104] in a study combined DL technique and augmented reality approaches in order to cater the fruitful information for the clients. They presented a mobile application such that it is able to locate the ...

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Automated Detection of Gender from Face Images

Automated Detection of Gender from Face Images

... Machine Learning - supervised, Image Processing - Digital images of the face region, Deep Learning - Convolutional Neural Network and Deep Learning - Tensor ...Supervised ...

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Machine Learning and Deep Learning

Machine Learning and Deep Learning

... Supervised learning: In supervised learning, algorithm builds a mathematical model from a set of data that contains both the input and desired ...this learning, algorithm receives a set of inputs ...

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PubMedCentral-PMC4832199.pdf

PubMedCentral-PMC4832199.pdf

... The experimental results show that the SDAE algorithm outperforms the conventional CADx algorithms on both applications. Specifically, as can be observed in Table 1, Figs 3 and 5, the SDAE algorithm can ...

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