KEYWORDS: Data modeling, Information fusion, Machine learning, Data fusion, Sensors, Systems modeling, Telecommunications, Artificial intelligence, Video, Image fusion
During the 2019 SPIE DSS conference, panelists were invited to highlight the trends and use of artificial intelligence and machine learning (AI/ML) for information fusion. The common themes between the panelists include leveraging AI/ML coordinated with Information Fusion for: (1) knowledge reasoning, (2) model building, (3) object recognition and tracking, (4) multimodal learning, and (5) information processing. The opportunity for machine learning exists within all the fusion levels of the Data Fusion Information Group model.
We propose a method to find characteristic landmarks and recognize ancient Roman imperial coins using deep convolutional neural networks (CNNs) combined with expert-designed domain hierarchies. We first propose a framework to recognize Roman coins that exploits the hierarchical knowledge structure embedded in the coin domain, which we combine with the CNN-based category classifiers. We next formulate an optimization problem to discover class-specific salient coin regions. Analysis of discovered salient regions confirms that they are largely consistent with human expert annotations. Experimental results show that the proposed framework is able to effectively recognize ancient Roman coins as well as successfully identify landmarks on the coins. For this research, we have collected a Roman coin dataset where all coins are annotated and consist of obverse (head) and reverse (tail) images.
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