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Found 6 papers, 4 papers with code
Arbitrarily-conditioned Data Imputation
In this paper, we propose an arbitrarily-conditioned data imputation framework built upon variational autoencoders and normalizing flows.
Images & Recipes: Retrieval in the cooking context
Recent advances in the machine learning community allowed different use cases to emerge, as its association to domains like cooking which created the computational cuisine.
Cross-Modal Retrieval in the Cooking Context: Learning Semantic Text-Image Embeddings
Designing powerful tools that support cooking activities has rapidly gained popularity due to the massive amounts of available data, as well as recent advances in machine learning that are capable of analyzing them.
Ranked #9 on
Cross-Modal Retrieval
on Recipe1M
Inspiring Computer Vision System Solutions
Reviewing this project with modern eyes provides us with the opportunity to reflect on several issues, relevant now as then to the field of computer vision and research in general, that go beyond the technical aspects of the work.
Deep Neural Networks Under Stress
In recent years, deep architectures have been used for transfer learning with state-of-the-art performance in many datasets.
Towards Automated Melanoma Screening: Proper Computer Vision & Reliable Results
In this paper we survey, analyze and criticize current art on automated melanoma screening, reimplementing a baseline technique, and proposing two novel ones.
