research
∙
07/26/2023
Resolution-Aware Design of Atrous Rates for Semantic Segmentation Networks
DeepLab is a widely used deep neural network for semantic segmentation, ...
share
research
∙
05/08/2023
Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields
Vision transformers (ViTs) that model an image as a sequence of partitio...
research
∙
02/13/2023
How to Use Dropout Correctly on Residual Networks with Batch Normalization
For the stable optimization of deep neural networks, regularization meth...
research
∙
02/07/2023
On the Ideal Number of Groups for Isometric Gradient Propagation
Recently, various normalization layers have been proposed to stabilize t...
research
∙
05/15/2022
Guidelines for the Regularization of Gammas in Batch Normalization for Deep Residual Networks
L2 regularization for weights in neural networks is widely used as a sta...
research
∙
11/16/2021
Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding
Vision transformers (ViTs) have recently demonstrated state-of-the-art p...
research
∙
08/31/2021
Dead Pixel Test Using Effective Receptive Field
Deep neural networks have been used in various fields, but their interna...
research
∙
01/15/2020
Extending Class Activation Mapping Using Gaussian Receptive Field
This paper addresses the visualization task of deep learning models. To ...
research
∙
06/24/2019
Data-driven prediction of vortex-induced vibration response of marine risers subjected to three-dimensional current
Slender marine structures such as deep-water marine risers are subjected...
research
∙
10/09/2018
