USGIF's Machine Learning and Artificial Intelligence Workshop will bring together a diverse group of individuals from government, industry, and academia to discuss current challenges and strategic initiatives related to the role of artificial intelligence, machine learning, cognitive computing, and deep learning in geospatial intelligence. We will be joined by today's visionary leaders in AI to explore this rapidly evolving and disruptive technology. Dr. C. Lee Giles, David Reese Professor of Information Sciences and Technology, and Interim Associate Dean of Research, Penn State University (invited) Dr. Nathan Jacobs, Associate Professor, Department of Computer Science, University of Kentucky Dr. Zsolt Kira, Branch Chief, Machine Learning and Analytics, Georgia Tech Research Institute Dr. Stella Yu, Director, Vision Group at the International Computer Science Institute, UC Berkeley Dr. C. Lee Giles, David Reese Professor of Information Sciences and Technology, and Interim Associate Dean of Research, Penn State University (invited)

Experimental research on Artificial Neural Network (ANN) algorithms requires either writing variations on the same program or making one monolithic program with many parameters and options. By using an object-oriented library, the size of these experimental programs is reduced while making them easier to read, write and modify. An efficient and flexible realization of this idea is Connectionist Layered Object-oriented Network Simulator (CLONES).

Experimental research on Artificial Neural Network (ANN) algorithms requires either writing variations on the same program or making one monolithic program with many parameters and options. By using an object-oriented library, the size of these experimental programs is reduced while making them easier to read, write and modify. An efficient and flexible realization of this idea is Connectionist Layered Object-oriented Network Simulator (CLONES).

Experimental research on Artificial Neural Network (ANN) algorithms requires either writing variations on the same program or making one monolithic program with many parameters and options. By using an object-oriented library, the size of these experimental programs is reduced while making them easier to read, write and modify. An efficient and flexible realization of this idea is Connectionist LayeredObject-oriented Network Simulator (CLONES).