Cluster-CAM: Cluster-Weighted Visual Interpretation of CNNs' Decision in Image Classification

• URL: http://arxiv.org/abs/2302.01642v1
• Date: Fri, 3 Feb 2023 10:38:20 GMT
• Title: Cluster-CAM: Cluster-Weighted Visual Interpretation of CNNs' Decision in Image Classification
• Authors: Zhenpeng Feng, Hongbing Ji, Milos Dakovic, Xiyang Cui, Mingzhe Zhu, Ljubisa Stankovic
• Abstract summary: Cluster-CAM is an effective and efficient gradient-free CNN interpretation algorithm. We propose an artful strategy to forge a cognition-base map and cognition-scissors from clustered feature maps.
• Score: 12.971559051829658
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Despite the tremendous success of convolutional neural networks (CNNs) in computer vision, the mechanism of CNNs still lacks clear interpretation. Currently, class activation mapping (CAM), a famous visualization technique to interpret CNN's decision, has drawn increasing attention. Gradient-based CAMs are efficient while the performance is heavily affected by gradient vanishing and exploding. In contrast, gradient-free CAMs can avoid computing gradients to produce more understandable results. However, existing gradient-free CAMs are quite time-consuming because hundreds of forward interference per image are required. In this paper, we proposed Cluster-CAM, an effective and efficient gradient-free CNN interpretation algorithm. Cluster-CAM can significantly reduce the times of forward propagation by splitting the feature maps into clusters in an unsupervised manner. Furthermore, we propose an artful strategy to forge a cognition-base map and cognition-scissors from clustered feature maps. The final salience heatmap will be computed by merging the above cognition maps. Qualitative results conspicuously show that Cluster-CAM can produce heatmaps where the highlighted regions match the human's cognition more precisely than existing CAMs. The quantitative evaluation further demonstrates the superiority of Cluster-CAM in both effectiveness and efficiency.

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