Preliminary Results on Distribution Shift Performance of Deep Networks for Synthetic Aperture Sonar Classification

Author:

Gerg Isaac D.1,Monga Vishal2

Affiliation:

1. Pennsylvania State University, University Park,Applied Research Laboratory,PA,USA

2. Pennsylvania State University, University Park,School of EECS,PA,USA

Funder

Experiment

Office of Naval Research

Publisher

IEEE

Reference45 articles.

1. EfficientNet: Rethinking model scaling for convolutional neural networks;tan;International Conference on Machine Learning,2019

2. EfficienNetV2: Smaller models and faster training;tan;International Conference on Machine Learning,2021

3. Deep Residual Learning for Image Recognition

4. A ConvNet for the 2020s

5. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;International Conference on Machine Learning,2015

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Uncovering Bias in Building Damage Assessment from Satellite Imagery;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. A Perceptual Metric Prior on Deep Latent Space Improves Out-Of-Distribution Synthetic Aperture Sonar Image Classification;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16

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