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[PDF] Top 20 Deep Transfer Learning for Art Classification Problems

Has 10000 "Deep Transfer Learning for Art Classification Problems" found on our website. Below are the top 20 most common "Deep Transfer Learning for Art Classification Problems".

Deep Transfer Learning for Art Classification Problems

Deep Transfer Learning for Art Classification Problems

... whether Deep Convolutional Neural Net- works (DCNNs), which have obtained state of the art results on the ImageNet challenge, are able to perform equally well on three different art ... Voir le document complet

16

Deep Learning for Classification of Hyperspectral Data: A Comparative Review

Deep Learning for Classification of Hyperspectral Data: A Comparative Review

... Deep Learning for Classification of Hyperspectral Data: A Comparative Review Nicolas Audebert, Bertrand Le Saux, Member, IEEE and S´ebastien Lef`evre Abstract—In recent years, deep ... Voir le document complet

14

Report Transfer Learning of Deep Convolutional Network on Twitter

Report Transfer Learning of Deep Convolutional Network on Twitter

... same pool of 1.6M positive and negative Stanford data. Though this is not really a good approximation but it works quite well in the litteratures ([4], [11]). The loss of the precision is hoped to become less important ... Voir le document complet

12

Training Compact Deep Learning Models for Video Classification Using Circulant Matrices

Training Compact Deep Learning Models for Video Classification Using Circulant Matrices

... architectures for video classification ...the art and conducted a series of experiments aiming at understanding the effect of compactness on different ... Voir le document complet

14

Uncertainty in predictions of deep learning models for fine-grained classification

Uncertainty in predictions of deep learning models for fine-grained classification

... used for a long time as a performance metric known as the top-k error ...rate. For instance, the top-5 error rate is the official metric of ImageNet (Russakovsky et ...used for standard ...losses ... Voir le document complet

134

Deep learning for classification and severity estimation of coffee leaf biotic stress.

Deep learning for classification and severity estimation of coffee leaf biotic stress.

... using Deep Learning for the problems of biotic stress classification and severity estimation of the most important coffee diseases and pests through leaf ...images. For the accomplishment ... Voir le document complet

9

Deep learning for classification and severity estimation of Coffee leaf biotic stress.

Deep learning for classification and severity estimation of Coffee leaf biotic stress.

... images. For the realization of all the experiments were used the proportions 70-15-15 for the training, validation and test datasets, ...features for a given problem. To make the training more ... Voir le document complet

11

Hyper-parameter optimization in deep learning and transfer learning : applications to medical imaging

Hyper-parameter optimization in deep learning and transfer learning : applications to medical imaging

... on deep leaning and how it could be used to solve medical imaging ...of deep learning and template deformation. Pre-deep learning methods were tailored for medical tasks, and ... Voir le document complet

117

Deep learning for cloud detection

Deep learning for cloud detection

... Conclusion Deep learning offers the possibility to build really complex and robust ...networks for cloud detection and to compare the resulting classification performance with ... Voir le document complet

7

Deep neural networks with transfer learning in millet crop images

Deep neural networks with transfer learning in millet crop images

... relevant for supervised learning, unsupervised learning, and reinforcement learning ( 2 ...of deep leaming have found solutions to many problems in image recognition and achieves ... Voir le document complet

7

Disease Classification in Metagenomics with 2D Embeddings and Deep Learning

Disease Classification in Metagenomics with 2D Embeddings and Deep Learning

... Figure 7: Performance comparison in MCC between our approach and Ph-CNN on external validation sets. Our results illustrate that the Fill-up approach out- performs the t-SNE. This may be due to several fac- tors. First, ... Voir le document complet

11

Urban object classification with 3D Deep-Learning

Urban object classification with 3D Deep-Learning

... and for each of these angles synthesise a 2D image representing the ...the classification. In term of accuracy they have the best results, for example, RotationNet [6] currently defines a new state ... Voir le document complet

5

Deep learning for cloud detection

Deep learning for cloud detection

... Conclusion Deep learning offers the possibility to build really complex and robust ...networks for cloud detection and to compare the resulting classification performance with ... Voir le document complet

8

Deep reinforcement learning for the control of conjugate heat transfer with application to workpiece cooling

Deep reinforcement learning for the control of conjugate heat transfer with application to workpiece cooling

... [22]) for control and opti- mization purposes of conjugate heat transfer systems, as governed by the coupled Navier–Stokes and heat ...methods for multiscale, multi-physics computational fluid ... Voir le document complet

33

A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series

A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series

... stage classification constitutes an important preliminary exam in the diagnosis of sleep ...first deep learning approach for sleep stage classification that learns end-to-end without ... Voir le document complet

13

Deep learning for urban remote sensing

Deep learning for urban remote sensing

... models for various remote sensing tasks: detection, classifi- cation or data ...used for classification and dense labeling of aerial ...and transfer knowledge [20], ...meta-data for ... Voir le document complet

5

Deep learning for continuous EEG analysis

Deep learning for continuous EEG analysis

... machine learning tech- niques and more specifically artificial neural networks, because they offer remarkable modeling possibilities on digital samples coming from continuous ...architecture for EEG ... Voir le document complet

146

A Multistage Deep Transfer Learning Method for Machinery Fault Diagnostics Across Diverse Working Conditions and Devices

A Multistage Deep Transfer Learning Method for Machinery Fault Diagnostics Across Diverse Working Conditions and Devices

... ABSTRACT Deep learning methods have promoted the vibration-based machinery fault diagnostics from manual feature extraction to an end-to-end solution in the past few years and exhibited great success on ... Voir le document complet

21

Comparison of deep transfer learning strategies for digital pathology

Comparison of deep transfer learning strategies for digital pathology

... of deep transfer learning in biomedical imaging were reported in [2, 6, 39] for pul- monary nodule detection in chest x-rays and CT-scans using Decaf and ...of deep transfer ... Voir le document complet

10

Transmitter Classification With Supervised Deep Learning

Transmitter Classification With Supervised Deep Learning

... supervised deep learning (SDL) has imposed itself as the tool to achieve state-of-the-art performance in many fields, starting with image processing to voice recognition, product suggestion, and more ... Voir le document complet

15

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