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Visual active learning for labeling: A case for soundscape ecology data
(2021-07-01)
Labeling of samples is a recurrent and time-consuming task in data analysis and machine learning and yet generally overlooked in terms of visual analytics approaches to improve the process. As the number of tailored ...
Evaluation of the accurateness of the nutritional labels of processed and ultra-processed products available in supermarkets of Ecuador
(2020)
Nutrition labeling is a public health tool that allows consumers to choose healthier foods and beverages. For this reason, there are protocols in place to monitor the food environment. The purpose of this study was to ...
Consumer Preference and Willingness to Pay for an Officially Certified Quality Label: Implications for Traditional Food Producers
(Instituto de Investigaciones Agropecuarias, INIA, 2007)
Confidence factor and feature selection for semi-supervised multi-label classification methodsFator de confid?ncia em sele??o de caracter?sticas para m?todos de classifica??o semi-supervisionado multi-r?tulo
(Instituto Federal de Educa??o, Ci?ncia e Tecnologia do Rio Grande do NorteBrasilParnamirimIFRN, 2017)
Compreensão da rotulagem nutricional por universitários da Universidade Tecnológica Federal do Paraná: Campus Londrina
(Universidade Tecnológica Federal do ParanáLondrinaBrasilTecnologia em AlimentosUTFPR, 2015-07-24)
The label function, among other things, is to guide consumers regarding the food itself, presenting the nutritional characteristics of the product, therefore clarify a healthy choice when buying. However, most consumers ...
A new multi-label dataset for Web attacks CAPEC classification using machine learning techniques
Context: There are many datasets for training and evaluating models to detect web attacks, labeling each request as normal or attack. Web attack protection tools must provide additional information on the type of attack ...