AZoOptics

Deep Learning in Optical Microscopy: Advancements and Applications

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.
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 ...
IEEE

Federated Coupled Contrastive Learning on Remote Sensing Image Classification

Abstract: Classification for Remote Sensing (RS) images plays a crucial role in various fields such as disaster assessment and urban planning. Nevertheless, due to resource limitations and privacy ...
Frontiers

Self-supervised transfer learning for few-shot classification on marine plankton images

The classification of marine plankton images is of great significance in ecological studies and environmental monitoring. In practical applications, plankton image classification faces several ...
Frontiers

Advancing Deep Learning Frameworks for Enhanced Cervical Cancer Diagnosis, Staging and Treatment

You will be redirected to our submission process. Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...
C&EN

Dual-Channel Multiscale Graph Transformer with Adversarial Contrastive Learning and Low-Rank Disentangled Stratified Negative Sampling for Drug Repositioning

State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing 211112, China ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
IEEE

Hierarchical and Bidirectional Contrastive Learning for Hyperspectral Image Classification

Abstract: Representing hyperspectral images (HSIs) is a complex and challenging task, primarily due to spectral uncertainty. The learnable prototypical contrastive learning is specialized in ...