Fractal graph convolutional network with MLP-mixer based multi-path feature fusion for classification of histopathological images
The spatial information among different tissue components and multi-level features is
important in histopathological images for pathologists to diagnose cancers. Graph …
important in histopathological images for pathologists to diagnose cancers. Graph …
Learning unsupervised parameter-specific affine transformation for medical images registration
Affine registration has recently been formulated using deep learning frameworks to establish
spatial correspondences between different images. In this work, we propose a new …
spatial correspondences between different images. In this work, we propose a new …
Online knowledge distillation by temporal-spatial boosting
Online knowledge distillation (KD) mutually trains a group of student networks from scratch
in a peer-teaching manner, eliminating the need for pre-trained teacher models. However …
in a peer-teaching manner, eliminating the need for pre-trained teacher models. However …
End-to-end data-dependent routing in multi-path neural networks
Neural networks are known to give better performance with increased depth due to their
ability to learn more abstract features. Although the deepening of networks has been well …
ability to learn more abstract features. Although the deepening of networks has been well …
[PDF][PDF] Data-dependent Resource Allocation and Routing in Multi-path Neural Networks for Vision-based Learning
MHGD Tissera - 2023 - researchgate.net
As the depth of a neural network increases, the non-linearity and more parameters allow it to
learn more complex functions. While network deepening has been proven effective, there is …
learn more complex functions. While network deepening has been proven effective, there is …