| Journal: | Computación y Sistemas |
| Database: | PERIÓDICA |
| System number: | 000456982 |
| ISSN: | 1405-5546 |
| Authors: | Pellegrin, Luis1 Loyola González, Octavio2 Ortiz Bejar, Jose3 Medina Pérez, Miguel Angel4 Gutiérrez Rodríguez, Andres Eduardo4 Tellez, Eric S5 Graff, Mario5 Miranda Jiménez, Sabino5 Moctezuma, Daniela5 García Limón, Mauricio6 Morales Reyes, Alicia6 Reyes García, Carlos A6 Morales, Eduardo6 Escalante, Hugo Jair6 |
| Institutions: | 1Universidad Autónoma de Baja California, Facultad de Ciencias, Ensenada, Baja California. México 2Instituto Tecnológico y de Estudios Superiores de Monterrey, Escuela de Ingeniería y Ciencias, Puebla. México 3Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán. México 4Instituto Tecnológico y de Estudios Superiores de Monterrey, Escuela de Ingeniería y Ciencias, Ciudad López Mateos. México 5Consejo Nacional de Ciencia y Tecnología, Ciudad de México. México 6Instituto Nacional de Astrofísica, Optica y Electrónica, Departamento de Informática, Tonantzintla, Puebla. México |
| Year: | 2019 |
| Season: | Oct-Dic |
| Volumen: | 23 |
| Number: | 4 |
| Pages: | 1305-1321 |
| Country: | México |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Descriptivo, crítico |
| English abstract | This paper describes the design of the 2017 RedICA: Text-Image Matching (RICATIM) challenge, including the dataset generation, a complete analysis of results, and the descriptions of the top-ranked developed methods. The academic challenge explores the feasibility of a novel binary image classification scenario, where each instance corresponds to the concatenation of learned representations of an image and a word. Instances are labeled as positive if the word is relevant for describing the visual content of the image, and negative otherwise. This novel approach of the image classification problem poses an alternative scenario where any text-image pair can be represented in such space, so any word could be considered for describing an image. The proposed methods are diverse and competitive, showing considerable improvements over the proposed baselines |
| Disciplines: | Ciencias de la computación |
| Keyword: | Inteligencia artificial, Procesamiento de datos, Programación, Coincidencia texto-imagen, Anotaciones, Procesamiento de información, Multimodalidad, Desafíos académicos |
| Keyword: | Artificial intelligence, Data processing, Programming, Text-image matching, Annotations, Information processing, Multimodality, Academic challenges |
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