Handbook of Research on Deep Learning Innovations and Trends by Hassanien Aboul Ella;Darwish Ashraf;Chowdhary Chiranji Lal;

Author:Hassanien, Aboul Ella;Darwish, Ashraf;Chowdhary, Chiranji Lal;
Language: eng
Format: epub
Publisher: IGI Global

Deep Learning is going to play a major role in near future in all field and area of research. It is predicted that in next five to ten years Deep Learning based tools, packages, libraries would become a standard component in every software applications. Some of the vital deep learning applications that will be predominant in 2018 and beyond are listed below.

1. Healthcare: Deep learning is extensively used in Breast or Skin Cancer diagnostics and also in prediction of personalized medicine on the basis of Biobank-data. Artificial Intelligence is completely reforming life sciences, medicine, and healthcare as an industry. Innovations in AI are succeeding the future medicine and population health management in incredible ways. Computer-aided detection, decision support tools, quantitative imaging, and computer-aided diagnosis will play a major role in years to come.

2. Voice Search and Voice-Activated Assistants: One of the most prevalent usage areas of deep learning is voice-activated intelligent assistants and voice search. Voice-activated assistants are present nearly in every smartphone. Apple’s Siri is one of the model which is on the market since October 2011. Google has launched voice-activated assistant for Android less than a year after Siri. Cortana is the newest voice-activated intelligent assistants by Microsoft.

3. Automatically Adding sounds to Silent Movies: The task of synthesizing the sound to match the silent video is an interesting task. The system is trained using 1000 examples of video with sound of a drumstick hitting various surfaces and creating diverse sounds. A deep learning model links the video frames with a database of pre-rerecorded sounds in order to select a sound to play that matches best with the scene. scene. The system is then evaluated using a turing-test like setup where humans had to determine which video is having the real or fake (synthesized) sounds. This uses application of both convolutional neural networks and Long short-term memory (LSTM) recurrent neural networks (RNN).

4. Automatic Machine Translation: The process of converting the words, phrases or sentence automatically from one language to another language is called Automatic Machine Translation. Deep learning has proved in these two specific areas:a. Automatic Translation of Text

b. Automatic Translation of Images

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