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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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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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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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Dynamic gesture classification of American Sign Language using deep learning
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Asm2Seq: Explainable Assembly Code Functional Summary Generation
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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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Abstract:
The goal of this research is to build a model to predict trend of financial asset price using sentiment from news headlines and financial indicators of the asset. Objective of the model is to conclude good results but also to minimize the difference between predicted values and actual values. Unlike previous approaches where the sentiments are usually calculated into score, we focus on combination of word embedding of news and financial indicators due to nonavailability of sentiment lexicon. One idea is that the sentiment of news headline should have impact on financial asset val- ues. In other words, it would be crucial how we extract information from news headlines. An- other idea is that price data through time series analysis is also useful to predict trend of financial asset prices. Hence, improvement should be made with combination of sentiment analysis of news headlines and time series analysis. Compared to time series models and word embedding models, our combined model shows smaller or similar small MAPE, MAE, and RMSE with time series models, and reduces lag in graphs.
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Keyword:
Finance and Financial Management; Long short-term memory; neural networks; Statistics and Probability; word embedding
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URL: https://digitalcommons.usf.edu/etd/8749 https://digitalcommons.usf.edu/cgi/viewcontent.cgi?article=9946&context=etd
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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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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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A study on the impact of neural architectures for Unsupervised Machine Translation
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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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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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