Doctorat en Intel·ligència Artificial
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Interoperating data-driven and model-driven techniques for the automated development of intelligent environmental decision support systems
(Elsevier, 2021-06)
Article
Restricted access - publisher's policyThis paper proposes an Intelligent Decision Support (IDS) methodology based on the integration of a data-driven technique —Case Based Reasoning (CBR)— and model-driven technique —Rule Based Reasoning (RBR)— for control, ... -
Forecastability measures that describe the complexity of a site for deep learning wind predictions
(2021-05-29)
Article
Open AccessThe application of deep learning to wind time series for multi-step prediction obtains good results at short horizons. The accuracy of a wind forecast is highly dependent on the specific structure of wind in the specific ... -
TALP at eHealth-KD Challenge 2020: Multi-level recurrent and convolutional neural networks for joint classification of key-phrases and relations
(CEUR-WS.org, 2020)
Conference report
Open AccessThis article describes the model presented by the TALP Team to IberLEF’s eHealth Knowledge Discovery 2020 shared task[1]. The model iterates over the idea of using a single model for simultaneously identify key-phrases and ... -
Real-time emotion classification using EEG data stream in e-learning contexts
(Multidisciplinary Digital Publishing Institute (MDPI), 2021-02-25)
Article
Open AccessIn face-to-face and online learning, emotions and emotional intelligence have an influence and play an essential role. Learners’ emotions are crucial for e-learning system because they promote or restrain the learning. ... -
Denoising wavefront sensor image with deep neural networks
(International Society for Photo-Optical Instrumentation Engineers (SPIE), 2020)
Conference report
Open AccessA classical closed-loop adaptive optics system with a Shack-Hartmann wavefront sensor (WFS) relies on a center of gravity approach to process the WFS information and an integrator with gain to produce the commands to a ... -
Effects of gamification in BCI functional rehabilitation
(2020-08-21)
Article
Open AccessOBJECTIVE: To evaluate whether introducing gamification in BCI rehabilitation of the upper limbs of post-stroke patients has a positive impact on their experience without altering their efficacy in creating motor mental ... -
Fusing hotel ratings and reviews with hesitant terms and consensus measures
(2020-02-27)
Article
Open AccessPeople have come to refer to reviews for valuable information on products before making a purchase. Digesting relevant opinions regarding a product by reading all the reviews is challenging. An automated methodology which ... -
Textual visual semantic dataset for text spotting
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Open AccessText Spotting in the wild consists of detecting and recognizing text appearing in images (e.g. signboards, traffic signals or brands in clothing or objects). This is a challenging problem due to the complexity of the context ... -
MetH: A family of high-resolution and variable-shape image challenges
(2019-11-20)
External research report
Open AccessHigh-resolution and variable-shape images have not yet been properly addressed by the AI community. The approach of down-sampling data often used with convolutional neural networks is sub-optimal for many tasks, and has ... -
Aplicación de la evaluación parcial a la metaprogramación
(1990)
External research report
Open AccessIf we apply partial evaluation to a meinterpreter and a program, we obtain another program that combines the functionalities of interpreter and the results of the program, without the inefficiency of the interpretation. ... -
Building graph representations of deep vector embeddings
(Association for Computational Linguistics, 2017)
Conference lecture
Open AccessPatterns stored within pre-trained deep neural networks compose large and powerful descriptive languages that can be used for many different purposes. Typically, deep network representations are implemented within vector ... -
Full-network embedding in a multimodal embedding pipeline
(Association for Computational Linguistics, 2017)
Conference lecture
Open AccessThe current state-of-the-art for image annotation and image retrieval tasks is obtained through deep neural networks, which combine an image representation and a text representation into a shared embedding space. In this ...
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