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Healthcare Big Data Management and Analytics in Scientific Programming
2021
Scientific Programming
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Some classification algorithms for EEG-based BCI systems are adaptive classifiers, tensor classifiers, transfer learning approach, and deep learning, as well as some miscellaneous approaches. ...
Visualization is a significant tool in producing diagrams, images, or animations to transfer healthcare messages and improve understandings. ...
Some classification algorithms for EEG-based BCI systems are adaptive classifiers, tensor classifiers, transfer learning approach, and deep learning, as well as some miscellaneous approaches. ...
doi:10.1155/2021/9780175
fatcat:lrcfhtnt3ndfzpeaczt4cl5jry
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning
2019
Nature Communications
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These vectors are used in image clustering and classification in a framework that enables mining of image sets for both novel and experienced users. ...
Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. ...
Here, we propose a visual programming approach to image analytics, where the users can combine image embedding by pretrained deep models with clustering and classification. ...
doi:10.1038/s41467-019-12397-x
pmid:31591416
pmcid:PMC6779910
fatcat:5lcfhhhsrfawvgxh3vp2cfq5ae
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes
[article]
2020
arXiv
pre-print
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In this paper, we present a visual analytics framework for the multi-level exploration of the transfer learning processes when training deep neural networks. ...
Despite recent advances in exploring deep learning models with visual analytics tools, little work has explored the issue of explaining and diagnosing the knowledge transfer process between deep learning ...
DISCUSSION AND CONCLUSIONS In this paper, we present a visual analytics framework for inspecting and exploring transfer learning processes. ...
arXiv:2009.06876v1
fatcat:ox7ru7il2bcivna4ubz7rqfxd4
P6: A Declarative Language for Integrating Machine Learning in Visual Analytics
[article]
2020
arXiv
pre-print
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By providing a declarative language for visual analytics, P6 can empower more developers to create visual analytics applications that combine machine learning and visualization methods for data analysis ...
We present P6, a declarative language for building high performance visual analytics systems through its support for specifying and integrating machine learning and interactive visualization methods. ...
ACKNOWLEDGMENTS This research is sponsored in part by the U.S. National Science Foundation through grant IIS-1741536 and IIS-1528203, and also by the U.S. ...
arXiv:2009.01399v1
fatcat:723jzwvs3nhkzkcajtl77uwvga
Rough Set Approach toward Data Modelling and User Knowledge for Extracting Insights
2021
Complexity
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Visualization is a key tool and has become one of the most significant platforms for interpreting, extracting, and communicating information. ...
The current study is an endeavour toward data modelling and user knowledge by using a rough set approach for extracting meaningful insights. ...
an approach of visual analytics for the visual data mining and interactive machine learning. ...
doi:10.1155/2021/7815418
fatcat:ihgqo5q4dbesdihegxyyeind2u
An Interactive Visual Analytics Tool for Big Earth Observation Data Content Estimation
2019
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
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This paper introduces a tool designed to provide an innovative and insightful way of exploring Earth observation data content beyond visualization, by addressing a visual analytics process. ...
The proposed tool-eVADE leverages the methodologies developed in the fields of information retrieval, data mining and knowledge representation by the means of a visual analytics component. eVADE increases ...
learning algorithms and state-of-the-art parallelization approaches in order to overcome limitations of big data processing An interactive system encompassing the visual analytics approach to explore the ...
doi:10.1109/igarss.2019.8898825
dblp:conf/igarss/FaurGSMD19
fatcat:u5ub3dq7ijfpfi7i5gj6fqaxpa
Data Analytics in the Internet of Things: A Survey
2019
Scalable Computing : Practice and Experience
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A comprehensive survey on the identified key enablers including their role in IoT data analytics, use cases in which they have been applied and the corresponding IoT applications for the use cases is presented ...
This article can be used as a basis to foster advanced research in the arena of IoT data analytics. ...
Apart from traditional machine learning approaches, various advanced learning approaches like deep learning, incremental learning, and transfer learning are also used to dig out valuable knowledge from ...
doi:10.12694/scpe.v20i4.1562
fatcat:y2fiya3q2bawhdg6hhczfpdbee
Do Machine Learning and Business Analytics Approaches Answer the Question of 'Will Your Kickstarter Project be Successful?
2021
Istanbul Business Research
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The data used for business analytics has been brought to a state that can provide inferences through visualization, reporting and query processes. ...
Within this scope, a business intelligence model that works on the web has been developed by combining business analytics and machine learning methods. ...
For this reason, a better classification can be made with both the selection of algorithms suitable for the data set and the ensemble approach. ...
doi:10.26650/ibr.2021.50.0117
fatcat:cocaeyoldbfdfo4ukw4poedxka
Large-Scale Social Multimedia Analysis
[chapter]
2019
Big Data Analytics for Large-Scale Multimedia Search
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for object detection and image classification on a subset of ImageNet, 1.2 million images over 1000 categories. ...
features extracted by a model-centric approach. ...
For available deep learning frameworks, refer to Torch [72] , Caffe [43] , MXNet [44] , Theano [73] , and TensorFlow [45] . ...
doi:10.1002/9781119376996.ch6
fatcat:dw4rzuqeanbvxmaabtsgrid2ty
Transfer Learning Based Traffic Sign Recognition Using Inception-v3 Model
2018
Periodica Polytechnica Transportation Engineering
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In this study, transfer learning-based method is introduced for traffic sign recognition and classification, which significantly reduces the amount of training data and alleviates computation expense using ...
The results show that transfer learning model can achieve a high-level recognition performance in traffic sign recognition, which is up to 99.18 % of recognition accuracy at 0.05 learning rate (average ...
Acknowledgements This work was supported by "Digital Fujian" Key Laboratory of Internet Things for Intelligent Transportation Technology, and funded by Chinese National Natural Fund for Young Scholars ...
doi:10.3311/pptr.11480
fatcat:vop3csztejhwpb7hj2qfj6lrdi
Privacy-Preserving Deep Inference for Rich User Data on The Cloud
[article]
2017
arXiv
pre-print
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In this paper, we present a hybrid approach for breaking down large, complex deep models for cooperative, privacy-preserving analytics. ...
Deep neural networks are increasingly being used in a variety of machine learning applications applied to rich user data on the cloud. ...
ACKNOWLEDGMENT We would like to thank Sina Sajadmanesh for his valuable comments and feedbacks. ...
arXiv:1710.01727v3
fatcat:q3tjyeptwvghrequjfae4dwb2y
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics
[article]
2019
arXiv
pre-print
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In this paper, we present a hybrid approach for breaking down large, complex deep neural networks for cooperative, privacy-preserving analytics. ...
Recently, advances in edge processing have paved the way for more efficient, and private, data processing at the source for simple tasks and lighter models, though they remain a challenge for larger, and ...
Transfer Learning. The result of transfer learning for different embeddings on different intermediate layers for both gender classification and activity recognition tasks are presented in Fig 9. ...
arXiv:1703.02952v7
fatcat:due6wly2x5acnavtq22eqwfi6a
Image Analytics for Legal Document Review: A Transfer Learning Approach
[article]
2019
arXiv
pre-print
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We use transfer learning techniques to leverage established pretrained models for feature extraction and fine tuning. ...
In this paper, we present several applications of deep learning in computer vision to Technology Assisted Review of image data in legal industry. ...
In the following sections we will present, for each of the applications, the business cases, the pretrained models used, and the transfer learning approaches. ...
arXiv:1912.12169v1
fatcat:xvtk7jl7m5cq5k5q6c5eankxx4
GCCE 2020 Subject Index
2020
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE)
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T U V W
Self-Attention Based Neural Network for Few Shot Classification
Self-Attention Based Neural Network for Few Shot Classification
Separation of Multiple Sound Sources in the Same Direction ...
by Instantaneous Spectral Estimation
Separation of Multiple Sound Sources in the Same Direction by Instantaneous Spectral Estimation
Sequence-To-One Neural Networks for Japanese Dialect Speech Classification ...
Suggestion in Transpiler for Rust Convert to RTL
Approach of a Japanese Co-Occurrence Words Collection Method for Construction of Linked Open Data for COVID-19 Approach of a Japanese Co-Occurrence Words ...
doi:10.1109/gcce50665.2020.9291796
fatcat:bmnnn7xnxrefhaneq262fe4i6u
Detection of COVID-19 in Chest X-ray Images: A Big Data Enabled Deep Learning Approach
2021
International Journal of Environmental Research and Public Health
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In this paper, the Apache Spark system has been utilized as an extensive data framework and applied a Deep Transfer Learning (DTL) method using Convolutional Neural Network (CNN) three architectures —InceptionV3 ...
But in COVID/Normal/pneumonia, detection accuracy was 97 percent for the inceptionV3 model, 98.55 percent for the ResNet50 Model, and 98.55 percent for the VGG19 model, respectively. ...
It can be easily used along with transfer learning for image classification. It has 16 layers. ...
doi:10.3390/ijerph181910147
pmid:34639450
fatcat:wc3vgctenzdlhl3rs5x4bsc73q
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