Proceedings of the National Academy of Sciences (PNAS)

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
GitHub

microCLIP: Unsupervised CLIP Adaptation via Coarse-Fine Token Fusion for Fine-Grained Image Classification

microCLIP is a lightweight self-training framework that adapts CLIP for fine-grained image classification without requiring labeled data. While CLIP is strong in zero-shot transfer, it primarily ...
EurekAlert!

Unsupervised cross-domain adaptation: single-pixel image transmission in unknown dynamic channels

Imaging technologies are ubiquitous in our daily lives, from smartphone cameras to medical imaging devices, helping us capture images and perceive objects. However, when faced with complex ...
IEEE

Distributed Unsupervised Representation Learning for Remote Sensing Image Classification

Abstract: With the development of in-orbit satellite hardware technology, distributed model training and updating for in-orbit satellites has become a promising trend. However, performance ...
IEEE

Masked Superpixel Contrastive Subspace Clustering Network for Unsupervised Large-Scale Hyperspectral Image Classification

Abstract: Subspace clustering (SSC) contributes a lot to the development of unsupervised hyperspectral image (HSI) classification task due to its ability of processing high-dimensional data. In ...
Frontiers

Training marine species object detectors with synthetic images and unsupervised domain adaptation

1 Australian Centre for Robotics, University of Sydney, Sydney, NSW, Australia 2 Department of Marine Technology, Norwegian University of Science and Technology, Trondheim, Norway Visual surveys by ...
Scientific Research Publishing

Conneau, A., et al. (2020) Unsupervised Cross-Lingual Representation Learning at Scale. Proceedings of ACL 2020, 5-10 July 2020, 8440-8451.

ABSTRACT: Natural Language Processing (NLP) has witnessed significant advancements, particularly with the development of multilingual models. However, a persistent challenge remains: the resource ...