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SIT740 Research and Development in Information Technology

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Recognition of Image and Machine Learning

The recognition of images is an important task to develop and test approaches of machine learning. The vision is a powerful sense which is available in humans naturally but the question remains in context to robotics on how to teach the robots to recognize images with accuracy.  Hence, this project has been chosen to identify a tool that will help to solve the issue. TensorFlow, an open source programming tool for dataflow has been chosen so that the concept behind recognition of images by robots can be easily implemented in the real world. The objective of this study is solve the concern regarding image recognition by robots.

In this study, a simulation program has been developed for implementing a prototype of the real life scenario. The advantage of this solution is that it will add as a security measure for household as well as commercial intelligent systems. The solution will also help to reduce the workload on humans to identify objects within an image during forensic investigations. The disadvantage of this solution is that it can operate properly only with the images that are stored in the database. The feature of the proposed solution is that it can be embedded with intelligent systems such that those can be used for commercial purposes.

Bibliography

Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M. and Kudlur, M., 2016, November. TensorFlow: A System for Large-Scale Machine Learning. In OSDI (Vol. 16, pp. 265-283).

Dean, J., 2015. Large-scale deep learning for intelligent computer systems. BayLearn keynote speech.

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