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- Title
CAM-K: a novel framework for automated estimating pixel area using K-Means algorithm integrated with deep learning based-CAM visualization techniques.
- Authors
Hacıefendioğlu, Kemal; Mostofi, Fatemeh; Toğan, Vedat; Başağa, Hasan Basri
- Abstract
This study proposed and implemented a novel framework that can automatically generate accurate area estimation of the identified brick-labeled pixels with the pixel-based intersection of union (IoU) technique. This novel framework employs a combination of fully convolutional neural network with class activation map and K-Means algorithm (CAM-K) to classify, visualize and calculate the pixel areas of brick-labeled images. The existing IoU method based on ground truth and estimated bounding boxes is not suitable for the calculation of localized pixel area. Experiment with our CAM-K framework revealed that it can reliably estimate the pixel areas of the detected object in classified images. Compared with the current state of IoU application, the proposed framework can realize specifically just those targeted pixels objects, and therefore, it can offer a far more realistic IoU metric.
- Subjects
DEEP learning; K-means clustering; CONVOLUTIONAL neural networks; PIXELS
- Publication
Neural Computing & Applications, 2022, Vol 34, Issue 20, p17741
- ISSN
0941-0643
- Publication type
Article
- DOI
10.1007/s00521-022-07428-6