scholarly journals A new Deep learning model for Sequential Pattern Mining using Ensemble learning and Models selection Taking Mobile Activity Recognition as a case

2019 ◽  
Vol 155 ◽  
pp. 129-136
Author(s):  
Choukri Djellali ◽  
Mehdi adda
Keyword(s):  
Deep Learning ◽  
Ensemble Learning ◽  
Activity Recognition ◽  
Pattern Mining ◽  
Learning Model ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Deep Learning Model

scholarly journals A Hybrid Deep Learning Model for Human Activity Recognition Using Multimodal Body Sensing Data

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 99152-99160 ◽  
Author(s):  
Abdu Gumaei ◽  
Mohammad Mehedi Hassan ◽  
Abdulhameed Alelaiwi ◽  
Hussain Alsalman
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Human Activity ◽  
Learning Model ◽  
Human Activity Recognition ◽  
Sensing Data ◽  
Deep Learning Model

scholarly journals Deep Learning Application to Ensemble Learning—The Simple, but Effective, Approach to Sentiment Classifying

2019 ◽  
Vol 9 (13) ◽  
pp. 2760 ◽  
Author(s):  
Khai Tran ◽  
Thi Phan
Keyword(s):  
Deep Learning ◽  
Sentiment Analysis ◽  
Ensemble Learning ◽  
Language Processing ◽  
Short Term Memory ◽  
Learning Model ◽  
Sentiment Classification ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Deep Learning Model

Sentiment analysis is an active research area in natural language processing. The task aims at identifying, extracting, and classifying sentiments from user texts in post blogs, product reviews, or social networks. In this paper, the ensemble learning model of sentiment classification is presented, also known as CEM (classifier ensemble model). The model contains various data feature types, including language features, sentiment shifting, and statistical techniques. A deep learning model is adopted with word embedding representation to address explicit, implicit, and abstract sentiment factors in textual data. The experiments conducted based on different real datasets found that our sentiment classification system is better than traditional machine learning techniques, such as Support Vector Machines and other ensemble learning systems, as well as the deep learning model, Long Short-Term Memory network, which has shown state-of-the-art results for sentiment analysis in almost corpuses. Our model’s distinguishing point consists in its effective application to different languages and different domains.

scholarly journals Hockey activity recognition using pre-trained deep learning model

ICT Express ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. 170-174
Author(s):  
Keerthana Rangasamy ◽  
Muhammad Amir As’ari ◽  
Nur Azmina Rahmad ◽  
Nurul Fathiah Ghazali
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Learning Model ◽  
Deep Learning Model

ST-DeepHAR: Deep Learning Model for Human Activity Recognition in IoHT Applications

2020 ◽  
pp. 1-1
Author(s):  
Mohamed Abdel-Basset ◽  
Hossam Hawash ◽  
Ripon K. Chakrabortty ◽  
Michael Ryan ◽  
Mohamed Elhoseny ◽  
...  
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Human Activity ◽  
Learning Model ◽  
Human Activity Recognition ◽  
Deep Learning Model
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