J
Jonathan J. Hull
Researcher at Ricoh
Publications - 335
Citations - 17059
Jonathan J. Hull is an academic researcher from Ricoh. The author has contributed to research in topics: Word recognition & Document management system. The author has an hindex of 72, co-authored 335 publications receiving 16583 citations. Previous affiliations of Jonathan J. Hull include University at Buffalo & State University of New York System.
Papers
More filters
Journal ArticleDOI
A database for handwritten text recognition research
TL;DR: An image database for handwritten text recognition research is described that contains digital images of approximately 5000 city names, 5000 state names, 10000 ZIP Codes, and 50000 alphanumeric characters to overcome the limitations of earlier databases.
Journal ArticleDOI
Decision combination in multiple classifier systems
TL;DR: This work proposes three methods based on the highest rank, the Borda count, and logistic regression for class set reranking that have been tested in applications of degraded machine-printed characters and works from large lexicons, resulting in substantial improvement in overall correctness.
Patent
Wireless image transfer from a digital still video camera to a networked computer
Jonathan J. Hull,John F Cullen +1 more
TL;DR: In this article, a portable image transfer system includes a digital still camera which captures images in digital form and stores the images in a camera memory, a cellular telephone transmitter, and a central processing unit (CPU).
Patent
Image matching and retrieval by multi-access redundant hashing
Jonathan J. Hull,Peter E. Hart +1 more
TL;DR: In this article, an improved document matching and retrieval system is disclosed where an input document is matched against a database of documents, using a descriptor database which lists descriptors and points to a list of documents containing features from which the descriptor is derived document.
Patent
Multimodal access of meeting recordings
TL;DR: In this article, a meeting recorder captures multimodal information of a meeting and subsequent analysis of the information produces scores indicative of visually and aurally significant events that can help identify significant segments of the meeting recording.