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Face Biometric Spoof Detection Method Using a Remote Photoplethysmography Signal
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In: Sensors; Volume 22; Issue 8; Pages: 3070 (2022)
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A Portable Sign Language Collection and Translation Platform with Smart Watches Using a BLSTM-Based Multi-Feature Framework
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In: Micromachines; Volume 13; Issue 2; Pages: 333 (2022)
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American Sign Language Words Recognition of Skeletal Videos Using Processed Video Driven Multi-Stacked Deep LSTM
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In: Sensors; Volume 22; Issue 4; Pages: 1406 (2022)
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Deep Learning Methods for Human Behavior Recognition
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Lu, Jia. - : Auckland University of Technology, 2021
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Can harbor seals ( Phoca vitulina ) discriminate familiar conspecific calls after long periods of separation?
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In: ISSN: 2167-8359 ; PeerJ ; https://hal.archives-ouvertes.fr/hal-03617108 ; PeerJ, PeerJ, 2021, 9, pp.e12431. ⟨10.7717/peerj.12431⟩ (2021)
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Learning emotions latent representation with CVAE for Text-Driven Expressive AudioVisual Speech Synthesis
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In: ISSN: 0893-6080 ; Neural Networks ; https://hal.inria.fr/hal-03204193 ; Neural Networks, Elsevier, 2021, 141, pp.315-329. ⟨10.1016/j.neunet.2021.04.021⟩ (2021)
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| 7 |
Human Gait Phase Recognition in Embedded Sensor System
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Liu, Zhenbang. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021
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| 8 |
Forecasting Hotel Room Occupancy Using Long Short-Term Memory Networks with Sentiment Analysis and Scores of Customer Online Reviews
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In: Applied Sciences ; Volume 11 ; Issue 21 (2021)
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Abstract:
For hotel management, occupancy is a crucial indicator. Online reviews from customers have gradually become the main reference for customers to evaluate accommodation choices. Thus, this study employed online customer rating scores and review text provided by booking systems to forecast monthly hotel occupancy using long short-term memory networks (LSTMs). Online customer reviews of hotels in Taiwan in various languages were gathered, and Google’s natural language application programming interface was used to convert online customer reviews into sentiment scores. Five other forecasting models—back propagation neural networks (BPNN), general regression neural networks (GRNN), least square support vector regression (LSSVR), random forest (RF), and gaussian process regression (GPR)—were employed to predict hotel occupancy using the same datasets. The numerical data indicated that the long short-term memory network model outperformed the other five models in terms of forecasting accuracy. Integrating hotel online customer review sentiment scores and customer rating scores can lead to more accurate results than using unique scores individually. The novelty and applicability of this study is the application of deep learning techniques in forecasting room occupancy rates in multilingual comment scenarios with data gathered from review text and customers’ rating scores. This study reveals that using long short-term memory networks with sentiment analysis of review text and customers’ rating scores is a feasible and promising alternative in forecasting hotel room occupancy.
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Keyword:
forecast; hotel room occupancy; long short-term memory networks; online reviews; sentiment analysis
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URL: https://doi.org/10.3390/app112110291
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| 9 |
Dynamic gesture classification of American Sign Language using deep learning
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| 10 |
Asm2Seq: Explainable Assembly Code Functional Summary Generation
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| 11 |
Combination of Time Series Analysis and Sentiment Analysis for Stock Market Forecasting
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In: Graduate Theses and Dissertations (2021)
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| 12 |
La memoria a lungo termine nell’invecchiamento. Implicazioni per l’educazione linguistica degli anziani
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In: Studi di glottodidattica; V. 6, N. 1 (2021): Volume 6 numero 1 anno 2021 - Supplemento; 29 - 43 ; 1970-1861 (2021)
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| 13 |
Generating Effective Sentence Representations: Deep Learning and Reinforcement Learning Approaches
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In: Electronic Thesis and Dissertation Repository (2021)
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| 14 |
A study on the impact of neural architectures for Unsupervised Machine Translation
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| 15 |
Sensory Descriptor Analysis of Whisky Lexicons through the Use of Deep Learning ; Foods
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Sensory Descriptor Analysis of Whisky Lexicons through the Use of Deep Learning ; FOODS
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| 17 |
An open-source voice type classifier for child-centered daylong recordings
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In: Interspeech 2020 - Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02989487 ; Interspeech 2020 - Conference of the International Speech Communication Association, Oct 2020, Shanghai / Virtual, China (2020)
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Audiovisual synthesis of expressive speech : modeling of emotions with deep learning ; Synthèse audiovisuelle de la parole expressive : modélisation des émotions par apprentissage profond
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In: https://hal.inria.fr/tel-03079349 ; Informatique [cs]. Université de Lorraine, 2020. Français. ⟨NNT : 2020LORR0137⟩ (2020)
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