Results 31 to 40 of about 3,349,947 (304)
From Composition to Acceptance: Linking Nutritional, Structural and Sensory Attributes in Clean-Label Breads [PDF]
FoodsThe growing demand for clean-label bakery products requires a deeper understanding of how functional ingredients and physicochemical properties shape consumer perception.
Manuela Sanna +5 more
doaj +2 more sources
Clean Label Meat Technology: Pre-Converted Nitrite as a Natural Curing [PDF]
Food Science of Animal Resources, 2021 Clean labeling is emerging as an important issue in the food industry, particularly for meat products that contain many food additives. Among synthetic additives, nitrite is the most important additive in the meat processing industry and is related to ...
Hae In Yong +5 more
doaj +2 more sources
Development of a Clean-Label Meat-Free Alternative to Deli Ham [PDF]
FoodsReducing meat consumption is a key strategy to mitigate environmental impact, lower the incidence of diet-related diseases, and promote sustainable food production. In response, the plant-based food market has grown significantly, motivated by demand for
Lisiane Carvalho +8 more
doaj +2 more sources
Clean-label backdoor attack on link prediction task
CybersecurityGraph Neural Networks (GNNs) have shown excellent performance as a powerful tool on link prediction task. Recent studies have shown that link prediction based on GNNs is vulnerable to backdoor attacks.
Junming Mo, Ming Xu, Xiaogang Xing
doaj +3 more sources
Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information [PDF]
Conference on Computer and Communications Security, 2022 Backdoor attacks introduce manipulated data into a machine learning model's training set, causing the model to misclassify inputs with a trigger during testing to achieve a desired outcome by the attacker. For backdoor attacks to bypass human inspection,
Yi Zeng +5 more
semanticscholar +1 more source
IEEE Access, 2023 Backdoor attacks, which induce a trained model to behave as intended by an adversary for specific inputs, have recently emerged as a serious security threat in deep learning-based classification models.
Tae-Hoon Kim +2 more
doaj +1 more source
Robust learning under clean-label attack
CoRR, 2021 We study the problem of robust learning under clean-label data-poisoning attacks, where the attacker injects (an arbitrary set of) correctly-labeled examples to the training set to fool the algorithm into making mistakes on specific test instances at test time.
Avrim Blum +3 more
openaire +4 more sources
Controlling Ingredients for Healthier Meat Products: Clean Label
Meat and Muscle Biology, 2020 Many ingredients are incorporated in the manufacture of meat products. Some of them are necessary to improve flavor, taste, and texture of meat products.
Geun Ho Kim, Ha Eun Kim, Koo Chin
doaj +2 more sources
Foods, 2023 Grass pea (Lathyrus sativus L.) is a pulse with historical importance in Portugal, but that was forgotten over time. Previous to this work, an innovative miso was developed to increase grass pea usage and consumption, using fermentation as a tool to ...
Sara Simões +5 more
doaj +1 more source
Adversarial Clean Label Backdoor Attacks and Defenses on Text Classification Systems [PDF]
Workshop on Representation Learning for NLP, 2023 Clean-label (CL) attack is a form of data poisoning attack where an adversary modifies only the textual input of the training data, without requiring access to the labeling function.
Ashim Gupta, Amrith Krishna
semanticscholar +1 more source