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Deep Learning and its Applications using Python
book

Deep Learning and its Applications using Python

by Niha Kamal Basha, Surbhi Bhatia Khan, Abhishek Kumar, Arwa Mashat
October 2023
Beginner to intermediate content levelBeginner to intermediate
256 pages
5h 42m
English
Wiley-Scrivener
Content preview from Deep Learning and its Applications using Python

10Conclusion

10.1 Introduction

In this chapter, a detailed discussion of new trends in deep learning, challenges in its direction, and prospects along with a practical case study are shown with working proofs. Some of the notable works highlighted in this chapter are given below from different domains, such as semantic intelligence, quantum AI, deep learning in cyber security domain, working of the LAMSTAR system, epilepsy seizure onset prediction, image processing for cancer detection, processing images from 2D images to 3D, image analysis for scene classification, fingerprint recognition, face recognition, butterfly species classification, leaf classification, traffic sign recognition, data classification from transcribed spoken conversation, speech recognition, music genre classification, credit card fraud detection, test drills to predict where to drill for oil, prediction of forest fires, price movement prediction in market microstructure and finally fault diagnosis via acoustic emission.

10.2 Future Research Direction and Prospects

Semantic Intelligence

A key topic in computer science is semantics, which offers a set of guidelines for deciphering various data kinds and enabling machines to comprehend the relationships and meanings of data. The immense volumes of data produced by the current world, including online data, databases, emails, images, videos, satellites, sensors, and smartphones, are dealt with by real semantic AI.

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Publisher Resources

ISBN: 9781394166466Purchase Link