Deep learning has transformed the automated analysis of cell images by enabling high‐throughput, accurate classification of subcellular patterns and morphological features. Convolutional neural ...

Few‐shot learning in image classification addresses the challenge of recognising new categories from only a handful of labelled examples. Traditional deep learning models rely on large annotated ...

A hierarchical deep-learning framework classified five lung and colon tissue classes with 98.50% accuracy on LC25000 and ...

A new deep learning framework that pairs super-resolution image enhancement with swarm-optimized transfer learning classified ...

Conceived an international research group, the proposed model uses the convolutional neural network (CNN) architecture U-Net for image segmentation and the the CNN architecture InceptionV3-Net for ...