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Found 7 papers, 1 papers with code
Separate Scene Text Detector for Unseen Scripts is Not All You Need
It raises a critical question: Is there a need for separate training for new scripts?
MTCD: Cataract Detection via Near Infrared Eye Images
We present deep learning-based eye segmentation and multitask network classification networks for cataract detection using NIR images as input.
Unravelling Small Sample Size Problems in the Deep Learning World
However, there are a lot of \textit{small sample size or $S^3$} problems for which it is not feasible to collect large training databases.
Generalized Zero-Shot Learning Via Over-Complete Distribution
A well trained and generalized deep neural network (DNN) should be robust to both seen and unseen classes.
Learning Structure and Strength of CNN Filters for Small Sample Size Training
The architecture provides the flexibility of training with both small and large training databases and yields good accuracies even with small size training data.
SegDenseNet: Iris Segmentation for Pre and Post Cataract Surgery
This paper presents an efficient iris segmentation algorithm with variations due to cataract and post cataract surgery.
