Effects of 2D and 3D Max Pooling on LSTMFeature Extraction-Reference-Cited by-同舟云学术

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Effects of 2D and 3D Max Pooling on LSTMFeature Extraction

Published:2023-12-14 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 20th India Council International Conference (INDICON)
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Author:

Bhattad Rashmi¹,Shah Arvik²,Patel Vibha³,Patel Samir²

Affiliation:

1. Gujarat Technological University,Department of Information Technology,Ahmedabad,India

2. Pandit Deendayal Energy University,SOT, Computer Science & Engineering,Gandhinagar,India

3. Vishwakarma Government Engineering College,Department of Information Technology,Chandkheda,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10440722/10440669/10440748.pdf?arnumber=10440748

Reference16 articles.

1. Visualizing and Understanding Convolutional Networks

2. Gradient-based learning applied to document recognition

3. 2. Striving for Simplicity

4. Breast tumor segmentation in automated 3D breast ultrasound using multi-view 2D convolutional neural networks;Xing;Medical image analysis,2020

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1. Deep learning fusion for dynamic cropland monitoring: integrating MUNet with Siamese networks and convolutional LSTM2D;Modeling Earth Systems and Environment;2024-06-26

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