Computer Vision

Multiple studies presented satisfactory performances for the treatment of various ocular diseases. To date, there has been no study …

The general framework for few-shot learning via kernel HyperNetworks—the fusion of kernels and hypernetwork paradigm is proposed, and it is shown that incorporating Bayesian neural networks into the general framework, an approach called BayesHyperShot, solves this issue.

In this study, we introduce a new synthetic data generation procedure for augmentation of histopathology image data. This is an …

In this study, we introduce a data augmentation procedure for histopathology image classification. This is an extension to our previous research, in which we showed the possibility to apply deep learning for morphological analysis of tumour cells.

This work proposes a novel neural network architecture capable of continual learning on 3D point cloud data by using rehearsal and reconstruction as regularization methods of the learning process and achieves a significant decrease of catastrophic forgetting.

The proposed HyperShot - the fusion of kernels and hypernetwork paradigm aims to switch the classification module parameters depending on the task’s embedding, and relies on relations between embeddings of the support examples instead of direct feature values provided by the backbone models.

In this study, we introduce a morphological analysis of segmented tumour cells from histopathology images concerning the recognition of cell overlapping. The main research problem considered is to distinguish how many cells are located in a structure, which is composed of overlapping cells.