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Green or clean? Perception of clean label plant-based products by omnivorous, vegan, vegetarian and flexitarian consumers [PDF]
[EN] Consumers are increasingly interested in health and sustainability aspects of their diets. Meat reduction diets have gained popularity with some consumers, leading to an increase in plant-based products in the markets.
Ana TERESA Noguerol +2 more
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Active cleaning of label noise
Pattern Recognition, 2016Mislabeled examples in the training data can severely affect the performance of supervised classifiers. In this paper, we present an approach to remove any mislabeled examples in the dataset by selecting suspicious examples as targets for inspection. We show that the large margin and soft margin principles used in support vector machines (SVM) have the
Ekambaram Rajmadhan +6 more
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Clean label: Why this ingredient but not that one?
Food Quality and Preference, 2021Abstract Consumer demand for natural and clean label foods continues to grow. This study aims to measure consumers’ perceived naturalness of food ingredients and further to investigate factors affecting their acceptability. Yogurt was chosen as the focal food of interest.
Nadia A Streletskaya, Juyun Lim
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Proceedings of the 13th International Symposium on Visual Information Communication and Interaction, 2020
One of the major problems of applying supervised machine learning methods in real-world problems is the absence of labeled data. Labeling huge amounts of data is time consuming and cost intensive. Moreover, in many cases, labels can only be assigned by domain experts like medical doctors or engineers, who have little time and do not necessarily have ...
David Beil, Andreas Theissler
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One of the major problems of applying supervised machine learning methods in real-world problems is the absence of labeled data. Labeling huge amounts of data is time consuming and cost intensive. Moreover, in many cases, labels can only be assigned by domain experts like medical doctors or engineers, who have little time and do not necessarily have ...
David Beil, Andreas Theissler
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Unknown Class Label Cleaning For Learning With Open-Set Noisy Labels
2020 IEEE International Conference on Image Processing (ICIP), 2020Deep neural networks (DNNs) trained on large-scale annotated datasets have achieved impressive results in the area of image classification. Many large-scale datasets have been collected from websites; however, such data are inevitably corrupted with noise.
Qing Yu 0013, Kiyoharu Aizawa
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Consumer perception of clean food labels
British Food Journal, 2022PurposeThis study puts forth a consumer-oriented concept of clean labels and attempts to empirically investigate consumer perceptions of these labels.Design/methodology/approachA self-administered survey (n = 346) was used as the research instrument for data collection in the current study.FindingsResults from an online survey indicate that consumers ...
Yan Cao, Li Miao
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Targeted Clean-Label Poisoning Attacks on Federated Learning
2023Federated Learning (FL) has become one of the most extensively utilized distributed training approaches since it allows users to access large datasets without really sharing them. Only the updated model parameters are exchanged with the central server after the model has been trained locally on the devices holding the data.
Ayushi Patel, Priyanka Singh 0001
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Euclidean distance based label noise cleaning
2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 2017Quality of the datasets play an important role in performance of supervised classifiers. In presence of mislabelled examples, the performance of such classifiers degrades severely. In this paper we propose a label noise cleaning approach based on euclidean distance.
Muhammad Ammar Malik, Moonsoo Kang
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Cleaning It Up—What Is a Clean Label Ingredient?
Cereal Foods World, 2015In this column, Busken looks at the process by which ingredients are made and uses this as a basis for determining whether they are “clean label” or not. One of the challenges in making this determination is presented by the degree to which even the simpler processes are performed and how they are dealt with in labeling laws.
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Automatic cleaning and labelling process for electrogastrogram
2018 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2018It is well known that recording electrical signals from the human body is a challenging task due to their nature and its vulnerability to noise effects. This is also the case of the electrogastrographic signal, the electrical activity of the digestive system that can be recorded using surface electrodes on the external wall of the abdomen.
Karina I. Espinosa-Espejel +3 more
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