Increment-CAM: Incrementally-Weighted Class Activation Maps for Better Visual Explanations
Author:
Affiliation:
1. Department of Computer Science and Engineering, Chung-Ang University, Seoul, South Korea
2. Department of Computer Science and Media Technology, Linnaeus University, Växjö, Sweden
Funder
Ministry of Science and Information and Communication Technology (ICT) and National IT Industry Promotion Agency (NIPA) through the High Performance Computing (HPC) Support Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/6287639/10380310/10556528.pdf?arnumber=10556528
Reference33 articles.
1. Electrospray mode discrimination with current signal using deep convolutional neural network and class activation map
2. Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorder using a deep learning model
3. Classification and visual explanation for COVID-19 pneumonia from CT images using triple learning
4. Understanding IFRA for Detecting Synchronous Machine Winding Short Circuit Faults Based on Image Classification and Smooth Grad-CAM++
5. CAMV: Class Activation Mapping Value Towards Open Set Fine-Grained Recognition
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