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ORCIDSusan P. Imberman
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2020 – today
- 2022
[c16]Susan P. Imberman:
Curricula Design in Public Interest Tech Using OER. SIGCSE (2) 2022: 1133- 2020
- [c15]Thaweesak Trongtirakul
, Werapon Chiracharit, Susan P. Imberman, Sos S. Agaian:
Fractional Contrast Stretching for Image Enhancement of Aerial and Satellite Images. Image Processing: Algorithms and Systems 2020
2010 – 2019
- 2019
- [j4]Susan P. Imberman, Ann Fiddler:
Share and share alike: : using Creative Commons licenses to create OER. Inroads 10(2): 16-21 (2019) - [c14]Susan P. Imberman, Robert J. Domanski:
Creating a Tech-in-Residence Corps of Industry Adjuncts: An Academic/Government/Industry Partnership. SIGCSE 2019: 1253 - 2017
- [c13]Susan P. Imberman, Jean McManus, Gina Otts:
Creating Serious Robots That Improve Society. AAAI 2017: 4781-4785 - 2015
- [j3]Susan P. Imberman:
Report on the special track in AI Education at FLAIRS 28. AI Matters 2(1): 12-13 (2015) - [c12]Susan P. Imberman, Michael E. Kress, Daniel P. McCloskey:
Exploring Equivalence Metrics to Analyze Behavior in a Naked Mole Rat Colony. FLAIRS 2015: 422-427 - 2013
- [c11]Susan P. Imberman, Sarah Zelikovitz, Irene Ludwig:
An Ophthalmologist's Tool for Predicting Deterioration in Patients with Accommodative Esotropia. ITNG 2013: 738-742 - 2012
- [c10]Susan P. Imberman, Michael E. Kress, Daniel P. McCloskey:
Using Frequent Pattern Mining To Identify Behaviors In A Naked Mole Rat Colony. FLAIRS 2012 - 2011
- [c9]Susan P. Imberman, Irene Ludwig, Sarah Zelikovitz:
Using Decision Trees to Find Patterns in an Ophthalmology Dataset. FLAIRS 2011 - [c8]Daniel P. McCloskey, Michael E. Kress, Susan P. Imberman, Igor Kushnir, Susan Briffa-Mirabella:
From market baskets to mole rats: using data mining techniques to analyze RFID data describing laboratory animal behavior. KDD 2011: 301-306 - [r1]Susan P. Imberman, Abdullah Uz Tansel:
Frequent Itemset Mining and Association Rules. Encyclopedia of Knowledge Management 2011: 343-353
2000 – 2009
- 2008
- [c7]Susan P. Imberman, Sarah Zelikovitz:
Robotics as a Component of a General Education Course. AAAI Spring Symposium: Using AI to Motivate Greater Participation in Computer Science 2008: 50-54 - 2007
- [c6]Susan P. Imberman, Aleksandr Barkan, Elizabeth Sklar:
Extra-Curricular Robotics: Entry-Level Soccer for Undergraduates. AAAI Spring Symposium: Semantic Scientific Knowledge Integration 2007: 59-64 - [c5]Susan P. Imberman, Roberta Klibaner, Sarah Zelikovitz:
Student Feedback on Robotics in CS1. AAAI Spring Symposium: Semantic Scientific Knowledge Integration 2007: 65-68 - [c4]Abdullah Uz Tansel, Susan P. Imberman:
Discovery of Association Rules in Temporal Databases. ITNG 2007: 371-376 - 2004
- [j2]Susan P. Imberman:
An intelligent agent approach for teaching neural networks using LEGO® handy board robots. ACM J. Educ. Resour. Comput. 4(3): 4:1-4:12 (2004) - 2003
- [c3]Susan P. Imberman:
Teaching neural networks using LEGO handy board robots in an artificial intelligence course. SIGCSE 2003: 312-316 - 2002
- [j1]Susan P. Imberman, Bernard Domanski, Hilary W. Thompson:
Using dependency/association rules to find indications for computed tomography in a head trauma dataset. Artif. Intell. Medicine 26(1-2): 55-68 (2002) - 2001
- [c2]Susan P. Imberman:
Effective Use of the KDD Process and Data Mining for Computer Performance Professionals. Int. CMG Conference 2001: 611-620
1990 – 1999
- 1999
- [c1]Susan P. Imberman, Bernard Domanski, Robert A. Orchard:
Using Booleanized Data To Discover Better Relationships Between Metrics. Int. CMG Conference 1999: 530-539
Coauthor Index
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