The research paper introduces MORPH, a pseudo-label-based concept drift adaptation method designed for neural networks to mitigate the challenges in malware detection. Concept drift refers to the shift in the…
Continue readingThe paper investigates the utility of conformal prediction sets in AI-advised decision-making. Through an experiment, it compares conformal prediction sets to displays of Top-1 and Top-k predictions for AI-advised image…
Continue readingThe article discusses the challenges in collecting cross-age facial images, which limits the versatility of supervised methods for age-invariant face recognition, a critical task in applications such as security and…
Continue readingThis paper discusses the use of denoising diffusion probabilistic models (DDPM) for medical image segmentation. The researchers highlight the challenges in this field, such as limited dataset sizes and the…
Continue readingThis article presents OTMatch, a new method for semi-supervised learning that leverages the semantic relationships among classes using an optimal transport loss function. The paper highlights that current algorithms often…
Continue readingThe article presents SemiReward, a new framework for semi-supervised learning (SSL). The main challenge of SSL is to distinguish high-quality pseudo labels against the confirmation bias. Current pseudo-label selection strategies…
Continue readingThe article presents a semi-supervised method for audio-visual speech recognition (AV-CPL), employing both labeled and unlabeled videos with continuously regenerated pseudo-labels. This method enables the recognition model to be trained…
Continue readingThis article discusses the use of semi-supervised learning and a teacher-student training approach to improve Music Information Retrieval (MIR) tasks. The authors scaled up unlabeled music data to 240k hours…
Continue readingThe article discusses a case study on annotating real estate images using a semi-supervised learning approach. The authors propose a model for automatic pre-selection of images from large unlabeled datasets…
Continue readingLooks like you're using an ad blocker. Please support us by disabling these ad blocker.
