CBAM: Convolutional Block Attention Module

Sanghyun Woo; Jongchan Park; Joon‐Young Lee; In So Kweon

doi:10.1007/978-3-030-01234-2_1

ScienceGate Book Chapters

BOOK-CHAPTER

CBAM: Convolutional Block Attention Module

Sanghyun Woo Jongchan Park Joon‐Young Lee In So Kweon

Year: 2018 Lecture notes in computer science Pages: 3-19 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-01234-2_1

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Feature (linguistics) Block (permutation group theory) Convolutional neural network Pattern recognition (psychology) Code (set theory) Artificial intelligence Algorithm Mathematics Programming language

Metrics

20526

Cited By

371.03

FWCI (Field Weighted Citation Impact)

Refs

1.00

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Adversarial Robustness in Machine Learning

Physical Sciences → Computer Science → Artificial Intelligence

CBAM: Convolutional Block Attention Module

Metrics

Citation History

Topics

Related Documents

A Lightweight Binarized Convolutional Block Attention Module: B-CBAM

Enhanced Breast Cancer Detection via Optimized Convolutional Block Attention Module (CBAM)

CBAM-GAN: Generative Adversarial Networks Based on Convolutional Block Attention Module

CBAM-LDNet: Convolutional Block Attention Module Based Lite DenseNet for Plant Disease Identification

CBAM-DeepConvNet: Convolutional Block Attention Module-Deep Convolutional Neural Network for asymmetric visual evoked potentials recognition