| Publication Type |
technical report |
| School or College |
College of Engineering |
| Department |
Computing, School of |
| Creator |
Ming, John C. |
| Title |
A multistrategy machine learning approach to object recognition |
| Date |
1991-03 |
| Description |
This work describes an innovative approach that combines machine learning and vision into an integrated system. The system is called ORACLE: Object Recognition Accomplished through Consolidation Learning Expertise. It uses two machine learning techniques known as explanation-based learning and conceptual clustering, combined in a synergistic manner, which provide effective object recognition. The learning system can automatically acquire new object models when unknown objects of interest are encountered in the environment. In addition, the object models are dynamic and qualitative in nature so they can be refined by the learning techniques during the recognition-learning cycle of the ORACLE system. Finally, the ORACLE system employs knowledge-based reasoning to effectively handle problems such as imprecise segmentation, image noise, and occlusion. |
| Type |
Text |
| Publisher |
University of Utah |
| Subject |
ORACLE; ORACLE system; computers |
| Subject LCSH |
Computer vision; Machine learning; Optical pattern recognition; Oracle (Computer file) |
| Language |
eng |
| Bibliographic Citation |
Ming, J. C. (1991). A multistrategy machine learning approach to object recognition. UUCS-91-05 |
| Series |
University of Utah Computer Science Technical Report |
| Relation is Part of |
ARPANET |
| Format Medium |
application/pdf |
| Format Extent |
157,203 Bytes |
| File Name |
Ming-A_Multistrategy_Machine.pdf |
| Conversion Specifications |
Original scanned with Kirtas 2400 and saved as 400 ppi uncompressed TIFF. PDF generated by Adobe Acrobat Pro X for CONTENTdm display |
| ARK |
ark:/87278/s60885dr |
| Setname |
ir_computersa |
| ID |
94876 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s60885dr |
