Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras

Autor: Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedito, Fernando Mateo, Antonio J. Serrano-López

Publikováno v: Applied Sciences, Vol 14, Iss 23, p 11075 (2024)

In this article, we propose the detection of crowd anomalies through the extraction of information in the form of time series in video format using a multimodal approach. Through pattern recognition algorithms and segmentation, informative measures o

Externí odkaz: https://doaj.org/article/4fa55f54245c4d7fbd8504e199562a51

Approaching sales forecasting using recurrent neural networks and transformers

Autor: Iván Vallés-Pérez, Emilio Soria-Olivas, Marcelino Martínez-Sober, Antonio J. Serrano-López, Juan Gómez-Sanchís, Fernando Mateo

Publikováno v: Vallés-Pérez, I., Soria-Olivas, E., Martínez-Sober, M., Serrano-López, A. J., Gómez-Sanchís, J., & Mateo, F. (2022). Approaching sales forecasting using recurrent neural networks and transformers. Expert Systems with Applications, 201, 116993.

Accurate and fast demand forecast is one of the hot topics in supply chain for enabling the precise execution of the corresponding downstream processes (inbound and outbound planning, inventory placement, network planning, etc). We develop three alte

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::432d97b8cb76554fbe46c6bcfd255e64
https://hdl.handle.net/10550/88380

End-to-end Keyword Spotting using Xception-1d

Autor: Iván Vallés-Pérez, Juan Gómez-Sanchis, Antonio J. Serrano-López, Joan Vila-Francés, Marcelino Martínez-Sober, Emilio Soria-Olivas

Publikováno v: ESANN 2021 proceedings.

The field of conversational agents is growing fast and there is an increasing need for algorithms that enhance natural interaction. In this work we show how we achieved state of the art results in the Keyword Spotting field by adapting and tweaking t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f11be61eae19db6f7289a378e8d6cb0c
https://doi.org/10.14428/esann/2021.es2021-21

A new visualization tool for data mining techniques

Autor: Emilio Soria-Olivas, José D. Martín-Guerrero, Antonio J. Serrano-López, José M. Martínez-Martínez, Pablo Escandell-Montero

Publikováno v: Progress in Artificial Intelligence. 5:137-154

Clustering techniques and classification trees are two of the main techniques used in data mining but, at present, there is still a lack of visualization methods for these tools. Many graphs associated with clustering, also with hierarchical clusteri

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1c2c9f388f60b3944305b6b974f3382b
https://doi.org/10.1007/s13748-015-0079-4

A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time

Autor: S. Martínez-Sanchis, Marcelino Martínez-Sober, J. A. Solves-Llorens, Antonio J. Serrano-López, José D. Martín-Guerrero, F. Martínez-Martínez, Carlos Monserrat, D. Lorente, Maria J. Ruperez-Moreno

Publikováno v: RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
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[EN] This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21a2622a5395bb04cfd0bd568c4ed350
https://doi.org/10.1016/j.compbiomed.2017.09.019