Grocery products detection and recognition is a very complex task because of the high variability in object appearances, and the possibly very large number of the products to be recognized. Here we present the results of our investigation in the classification of grocery products. We tested several CNN architectures trained in different modalities for product classification, and we propose a multi-task learning network to be used as feature extractor. We evaluated the features extracted from the networks in both supervised and unsupervised classification scenarios. All the experiments have been conducted on publicly available datasets in the literature.

Ciocca, G., Napoletano, P., Locatelli, S. (2021). Multi-task Learning for Supervised and Unsupervised Classification of Grocery Images. In Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10–15, 2021, Proceedings, Part II (pp.325-338). Springer International Publishing [10.1007/978-3-030-68790-8_26].

Multi-task Learning for Supervised and Unsupervised Classification of Grocery Images

Ciocca, Gianluigi;Napoletano, Paolo
;
2021

Abstract

Grocery products detection and recognition is a very complex task because of the high variability in object appearances, and the possibly very large number of the products to be recognized. Here we present the results of our investigation in the classification of grocery products. We tested several CNN architectures trained in different modalities for product classification, and we propose a multi-task learning network to be used as feature extractor. We evaluated the features extracted from the networks in both supervised and unsupervised classification scenarios. All the experiments have been conducted on publicly available datasets in the literature.
slide + paper
Supervised classification, Clustering, Convolutional Neural Networks, Grocery product recognition
English
25th International Conference on Pattern Recognition
2021
Del Bimbo, Alberto; Cucchiara, Rita; Sclaroff, Stan; Farinella, Giovanni Maria; Mei, Tao; Bertini, Marco; Escalante, Hugo Jair; Vezzani, Roberto
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10–15, 2021, Proceedings, Part II
978-3-030-68789-2
2021
12662
325
338
none
Ciocca, G., Napoletano, P., Locatelli, S. (2021). Multi-task Learning for Supervised and Unsupervised Classification of Grocery Images. In Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10–15, 2021, Proceedings, Part II (pp.325-338). Springer International Publishing [10.1007/978-3-030-68790-8_26].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/308427
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