Publications
2021
1.
Saikia, Surajit; Fernández-Robles, Laura; Fidalgo, Eduardo; Alegre, Enrique
Colour Neural Descriptors for Instance Retrieval Using CNN Features and Colour Models Artículo de revista
En: IEEE Access, vol. 9, pp. 23218–23234, 2021, (Publisher: IEEE).
Resumen | Enlaces | BibTeX | Etiquetas: CNN Features, Color Descriptors, deep learning, Image Retrieval, Object Detection
@article{saikia_colour_2021,
title = {Colour Neural Descriptors for Instance Retrieval Using CNN Features and Colour Models},
author = {Surajit Saikia and Laura Fernández-Robles and Eduardo Fidalgo and Enrique Alegre},
url = {https://ieeexplore.ieee.org/abstract/document/9344701},
year = {2021},
date = {2021-01-01},
journal = {IEEE Access},
volume = {9},
pages = {23218–23234},
abstract = {This paper presents color neural descriptors for image retrieval, using CNN features from different color spaces without fine-tuning. An object detector enhances feature extraction, and a stride-based query expansion improves multi-view retrieval. The method achieves state-of-the-art results on multiple datasets.},
note = {Publisher: IEEE},
keywords = {CNN Features, Color Descriptors, deep learning, Image Retrieval, Object Detection},
pubstate = {published},
tppubtype = {article}
}
This paper presents color neural descriptors for image retrieval, using CNN features from different color spaces without fine-tuning. An object detector enhances feature extraction, and a stride-based query expansion improves multi-view retrieval. The method achieves state-of-the-art results on multiple datasets.
0000
2.
Fidalgo, Eduardo; Fernández-Robles, Laura; García-Ordás, Maite; Olivera, Óscar García-Olalla; Alegre, Enrique
EVALUATION OF SHAPE AND COLOR DESCRIPTORS BY USING BAG OF WORD TECHNIQUES WITH ONE VS ALL CLASSIFICATION Artículo de revista
En: 0000.
Resumen | Enlaces | BibTeX | Etiquetas: Bag of Words, Color Descriptors, One-vs-all, Shape Description
@article{fidalgo_evaluation_nodate,
title = {EVALUATION OF SHAPE AND COLOR DESCRIPTORS BY USING BAG OF WORD TECHNIQUES WITH ONE VS ALL CLASSIFICATION},
author = {Eduardo Fidalgo and Laura Fernández-Robles and Maite García-Ordás and Óscar García-Olalla Olivera and Enrique Alegre},
url = {https://www.researchgate.net/profile/Eduardo-Fidalgo-4/publication/257758029_Evaluation_of_shape_and_color_descriptors_by_using_bag_of_Word_techniques_with_one_vs_all_classification/links/5a2032d8458515341c85589a/Evaluation-of-shape-and-color-descriptors-by-using-bag-of-Word-techniques-with-one-vs-all-classification.pdf},
abstract = {This paper evaluates various shape and color descriptors on two datasets: “Soccer” and a newly introduced one called “Karinas_Dataset1.” Images are represented using descriptors created through the Bag of Words (BoW) technique. A one-vs-all classifier is then trained and tested with random images from the datasets. To avoid outliers, experiments are repeated 10 times and the average result is reported.},
keywords = {Bag of Words, Color Descriptors, One-vs-all, Shape Description},
pubstate = {published},
tppubtype = {article}
}
This paper evaluates various shape and color descriptors on two datasets: “Soccer” and a newly introduced one called “Karinas_Dataset1.” Images are represented using descriptors created through the Bag of Words (BoW) technique. A one-vs-all classifier is then trained and tested with random images from the datasets. To avoid outliers, experiments are repeated 10 times and the average result is reported.