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Author  |
Henry O. Velesaca, Angel D. Sappa & Juan A. Holgado |
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Title |
A Case Study of Anomaly Detection in Tinplate Lids: Supervised vs Unsupervised approaches |
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2025 |
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11th International Conference on Automation, Robotics, and Applications (ICARA 2025) |
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cidis @ cidis @ |
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267 |
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Author |
Henry O. Velesaca, Gisel Bastidas, Mohammad Rouhani, Angel D. Sappa |
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Title |
Multimodal image registration techniques: a comprehensive survey |
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Year |
2024 |
Publication |
Multimedia Tools and Applications |
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Vol. 83 |
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63919 - 63947 |
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13807501 |
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cidis @ cidis @ |
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248 |
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Henry Velesaca, Boris Vintimilla, Jorge Vulgarin, Coen Antens & Alberto Rubio Pérez |
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Title |
Deep Learning-based Multimodal Sensing Framework for AntiSpoofing Systems |
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Journal Article |
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2024 |
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Lecture Notes in Networks and Systems: 4th International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) |
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Vol. 1116 LNNS |
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39-54 |
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23673370 |
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978-981976994-0 |
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cidis @ cidis @ |
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238 |
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Author |
Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa |
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Title |
Fine-tuning deep convolutional networks for lepidopterous genus recognition |
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2017 |
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Lecture Notes in Computer Science |
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Vol. 10125 LNCS |
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pp. 467-475 |
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gtsi @ user @ |
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63 |
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Author |
Juca Aulestia M., Labanda Jaramillo M., Guaman Quinche J., Coronel Romero E., Chamba Eras L., & Roberto Jacome Galarza |
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Title |
Open innovation at university: a systematic literature review |
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Journal Article |
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Year |
2020 |
Publication |
Advances in Intelligent Systems and Computing |
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1159 AISC, 2020 |
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3-14 |
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Call Number |
cidis @ cidis @ |
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189 |
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Author |
Leo Ramos & Angel D. Sappa |
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Title |
Multispectral Semantic Segmentation for Land Cover Classification: An Overview |
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Year |
2024 |
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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Vol. 17 |
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14295-14336 |
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19391404 |
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cidis @ cidis @ |
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250 |
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Author |
Leo Thomas Ramos & Angel D. Sappa |
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Title |
Leveraging U-Net and selective feature extraction for land cover classification using remote sensing imagery |
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Year |
2025 |
Publication |
Scientific Reports |
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Vol. 15 |
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cidis @ cidis @ |
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270 |
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Author |
Luis Chuquimarca, Boris Vintimilla & Sergio Velastin |
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Title |
A Review of External Quality Inspection for Fruit Grading using CNN Models |
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Year |
2024 |
Publication |
Artificial Intelligence in Agriculture |
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Vol. 14 |
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Pages |
1-20 |
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ISSN |
25897217 |
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Call Number |
cidis @ cidis @ |
Serial |
254 |
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Author |
Ma. Paz Velarde; Erika Perugachi; Dennis G. Romero; Ángel D. Sappa; Boris X. Vintimilla |
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Title |
Análisis del movimiento de las extremidades superiores aplicado a la rehabilitación física de una persona usando técnicas de visión artificial. |
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Journal Article |
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Year |
2015 |
Publication |
Revista Tecnológica ESPOL-RTE |
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Vol. 28 |
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pp. 1-7 |
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Keywords |
Rehabilitation; RGB-D Sensor; Computer Vision; Upper limb |
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Abstract |
Comúnmente durante la rehabilitación física, el diagnóstico dado por el especialista se basa en observaciones cualitativas que sugieren, en algunos casos, conclusiones subjetivas. El presente trabajo propone un enfoque cuantitativo, orientado a servir de ayuda a fisioterapeutas, a través de una herramienta interactiva y de bajo costo que permite medir los movimientos de miembros superiores. Estos movimientos son capturados por un sensor RGB-D y procesados mediante la metodología propuesta, dando como resultado una eficiente representación de movimientos, permitiendo la evaluación cuantitativa de movimientos de los miembros superiores. |
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ESPOL |
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English |
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English |
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Call Number |
cidis @ cidis @ |
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39 |
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Author |
Marjorie Chalen; Boris X. Vintimilla |
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Title |
Towards Action Prediction Applying Deep Learning |
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Year |
2019 |
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Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 |
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pp. 1-3 |
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Keywords |
action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm. |
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Abstract |
Considering the incremental development future action prediction by video analysis task of computer vision where it is done based upon incomplete action executions. Deep learning is playing an important role in this task framework. Thus, this paper describes recently techniques and pertinent datasets utilized in human action prediction task. |
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Call Number |
cidis @ cidis @ |
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129 |
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