54 citations · 70 across the 6 of their papers we have counts for
7 papers
Stochastic-based Patch Filtering for Few-Shot Learning
Javier Rodenas, Eduardo Aguilar, Petia Radeva
Food images present unique challenges for few-shot learning models due to their visual complexity and variability. For instance, a pasta dish might appear with various garnishes on…
Slot Attention-based Feature Filtering for Few-Shot Learning
Javier Rodenas, Eduardo Aguilar, Petia Radeva
Irrelevant features can significantly degrade few-shot learn ing performance. This problem is used to match queries and support images based on meaningful similarities despite the…
Multi-label out-of-distribution detection via evidential learning
Eduardo Aguilar, Bogdan Raducanu, Petia Radeva
A crucial requirement for machine learning algorithms is not only to perform well, but also to show robustness and adaptability when encountering novel scenarios. One way to achiev…
Continual Evidential Deep Learning for Out-of-Distribution Detection
Eduardo Aguilar, Bogdan Raducanu, Petia Radeva +1
Uncertainty-based deep learning models have attracted a great deal of interest for their ability to provide accurate and reliable predictions. Evidential deep learning stands out a…
Grab, Pay and Eat: Semantic Food Detection for Smart Restaurants
Eduardo Aguilar, Beatriz Remeseiro, Marc Bolaños +1
The increase in awareness of people towards their nutritional habits has drawn considerable attention to the field of automatic food analysis. Focusing on self-service restaurants…
Food Recognition using Fusion of Classifiers based on CNNs
Eduardo Aguilar, Marc Bolaños, Petia Radeva
With the arrival of convolutional neural networks, the complex problem of food recognition has experienced an important improvement in recent years. The best results have been obta…
Exploring Food Detection using CNNs
Eduardo Aguilar, Marc Bolaños, Petia Radeva
One of the most common critical factors directly related to the cause of a chronic disease is unhealthy diet consumption. In this sense, building an automatic system for food analy…