J
James Z. Wang
Researcher at Pennsylvania State University
Publications - 234
Citations - 23185
James Z. Wang is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Image retrieval & Automatic image annotation. The author has an hindex of 57, co-authored 225 publications receiving 21890 citations. Previous affiliations of James Z. Wang include Penn State College of Information Sciences and Technology & University of Minnesota.
Papers
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Proceedings ArticleDOI
Algorithmic inferencing of aesthetics and emotion in natural images: An exposition
TL;DR: The aesthetics gap is defined and key aspects of the problem of aesthetics and emotion inference in natural images are discussed, including precise, relevant questions to be answered, the effect that the target audience has on the problem specification, broad technical solution approaches, and assessment criteria.
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Rhythmic Brushstrokes Distinguish van Gogh from His Contemporaries: Findings via Automated Brushstroke Extraction
TL;DR: It is confirmed that the combined brushwork features identified as special to van Gogh are consistently held throughout his French periods of production (1886-1890).
Proceedings ArticleDOI
RIME: A replicated image detector for the World-Wide Web
TL;DR: This paper describes RIME (Replicated IMage dEtector), an alternative approach to watermarking for detecting unauthorized image copying on the Internet and shows that it can detect image copies effectively.
Proceedings ArticleDOI
On shape and the computability of emotions
TL;DR: This work combines shape features with other state-of-the-art features to show a gain in prediction and classification accuracy and model emotions from a dimensional perspective in order to predict valence and arousal ratings which have advantages over the traditional discrete emotional categories.
Journal ArticleDOI
The Story Picturing Engine---a system for automatic text illustration
TL;DR: An unsupervised approach to automated story picturing by extracting semantic keywords from the story, an annotated image database is searched and a novel image ranking scheme automatically determines the importance of each image.