1. Soft Computing Lecture 21 Review of using of NN for solving of real tasks

2. 07.12.20052 Autopilot airplane LoFLYTE (Low-Observable Flight Test Experiment) is developed for NASA and USA Air Force by Accurate Automation Corp., Chattanooga, TN. Speed is 4-5 M NN is learning by pilot (storing associations between situation and action of pilot) and after that may control without pilot

3. 07.12.20053 Project TNA System for searching of plastic explosive in baggage in airports is developed by SAIC (Science Application International Corporation) NN analyzes of spectrum of baggage after irradiation of it by slow neutrons Recognition of explosive with probability 97%, speed is 10 units per minute

4. 07.12.20054 Using of NN on financial markets Citibank uses NN from 1990. In 1992 yield was 25% which is large more then most of brokers Chemical Bank uses NN (from company Neural Data) for previous processing of transactions in currency exchanges in 23 countries for detection of shady bargains Fidelity of Boston uses NN for control of portfolio with volume 3 billion USA, Deere & Co – 100 million USA, LBS Capital – 400 million USA Proceedings of one seminar “AI in Wall Street” includes 6 large volumes.

5. 07.12.20055 Recognition of stolen credit cards Developer is HNC Software Corp., now Fair Isaac Corporation http://www.fairisaac.com Software Falcon based on NN This company controls more then 220 million accounts NN is learning to recognize unusual behavior of clients with credit card

6. 07.12.20056 Active reclaim in Internet Developer is Aptex Software Inc. Software SelectCast based on NN NN is learning by interesting of users and offers to client such reclaim which may be interesting for him

7. 07.12.20057 Control of mobile robots LSTM for robots Planning of path and navigation Recognition of objects

8. 07.12.20058 Camera-robot coordination is function approximation The system we focus on in this section is a work floor observed by a fixed cameras and a robot arm. The visual system must identify the target as well as determine the visual position of the end-effector.

9. 07.12.20059 Camera-robot coordination is function approximation (2)

10. 07.12.200510 Camera-robot coordination is function approximation (3). Two approach to use neural networks: Usage of feed-forward networks –Indirect learning –General learning –Specialized learning Usage of topology conserving maps

11. 07.12.200511 Camera-robot coordination is function approximation (4). feed-forward networks Indirect learning system for robotics. In each cycle the network is used in two different places: first in the forward step then for feeding back the error

12. 07.12.200512 Camera-robot coordination is function approximation (5). feed-forward networks (2)

13. 07.12.200513 Sensor based control

14. 07.12.200514 The structure of the network for the autonomous land vehicle

15. 07.12.200515 Drama

16. 07.12.200516 Diagnosis of cancer Yulei Jiang, assistant professor of radiology at the University of Chicago System that uses a perceptron neural network to analyze eight input nodes, converting the output node into a robability measure, which Jiang calls likelihood of malignancy. The system is trained on a set of cases, using the leave- one-out method, which is a cross-validation technique for estimating generalization error based on resampling. A net is trained a number of times, each time leaving out one of the subsets. The omitted subset computes whatever error criterion is of interest. The system initially learns from digitized screen mammograms. The eight input nodes represent features of calcifications, areas in breast tissue where tiny calcium deposits build up and might indicate the presence of cancer.

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