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Found 6 papers, 2 papers with code
Learning to Classify New Foods Incrementally Via Compressed Exemplars
Therefore, food image classification systems should adapt to and manage data that continuously evolves.
Probing Image Compression For Class-Incremental Learning
To this end, we introduce a new framework to incorporate image compression for continual ML including a pre-processing data compression step and an efficient compression rate/algorithm selection method.
Towards Backward-Compatible Continual Learning of Image Compression
This paper explores the possibility of extending the capability of pre-trained neural image compressors (e. g., adapting to new data or target bitrates) without breaking backward compatibility, the ability to decode bitstreams encoded by the original model.
A Visual Quality Assessment Method for Raster Images in Scanned Document
Different from many existing works which aim to estimate a visual quality score, we propose a machine learning based classification method to determine whether the visual quality of a scanned raster image at a given resolution setting is acceptable.
Visual communication of object concepts at different levels of abstraction
People can produce drawings of specific entities (e. g., Garfield), as well as general categories (e. g., "cat").
Deepfakes Detection with Automatic Face Weighting
Altered and manipulated multimedia is increasingly present and widely distributed via social media platforms.
