Deep learning, in particular, is the new frontier for the video industry, allowing video professionals to do things automatically that would have taken weeks of work in the past, as well as some things that wouldn't have been possible at all. How is deep learning different from other machine learning algorithms? And what are its practical applications for broadcasting and filmed entertainment? What are the science and its business ramifications?

1. How Deep Learning
could revolutionize
broadcasting…

2. Presented By
S. K. M Shadekul Islam- 191-15- 12836
Presenter To
Md Sanzidul Kawser
Lecturer
Department of CSE
Daffodil International University
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3. Artificial Intelligence, Machine Learning, and
Deep Learning
Artificial intelligence is any attempt to make a computer appear as though it has
intelligence. The computer may be told exactly what to do in any given situation, in
which case it hasn't learned anything. Machine learning seeks to allow the
computer to learn how to perform certain tasks. There are a variety of methods to
do this, and nearly all of them rely on the computer altering parameters repeatedly
through a trial and error process. One of the more complex ways of doing this is by
mimicking the neurons in a biological brain. When we make these artificial brains,
or neural networks, more complex, we have Deep Learning.
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4. Deep learning for TV and Filmed
Entertainment
There are many opportunities to apply deep learning techniques in the field of
video production, video editing, and cataloging. But the technology is not limited to
automating repetitive tasks; it can also enhance the creative process, improve video
delivery and help preserve the massive video archives that many studios keep.
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5. Video Generation and Editing
Consumer-grade, easy to use solutions such as Flo allow you to use deep learning to
automatically create a video by describing what you want in it. The software will
find the relevant videos from your library and edit them together automatically.
Google has a neural network that can automatically separate the foreground and
background of a video. What used to require a green screen can now be done with
no special equipment.
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6. Video Restoration
According to the UCLA Film & Television Archive, nearly half of all films
produced prior to 1950 have disappeared. Worse, 90% of the classic film prints
that do exist are in poor condition. The process of restoring these films is long,
tedious, and expensive. This is an area in which deep learning is going to make a
major difference.
Thanks to Nvidia, deep learning can now speed up the process significantly, with
tools that only require an artist to color one frame of a scene. From there, the deep
learning network automatically handles the rest.
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7. Face/Object Recognition
By detecting the faces of everyone in a video, deep learning can allow you to quickly
classify a video collection. You could, for example, search for any clip or movie that
has a given performer. Alternatively, you could use the technology to count the
exact screen time for every actor in a video. Sky News recently used facial
recognition to identify famous faces at the royal wedding.
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8. Video Analysis
While Flo can identify what a scene is about and use that data to generate a video
about whatever you want, that same technology can be used to sort and classify
videos to make it easy to find a particular piece of footage by simply searching for
people or actions that appear in it.
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9. Better Streaming
As we move into 4k streaming, and television manufacturers begin the rollout of 8k
displays, streaming is using more data than ever before. Anyone with a poor
connection knows what a problem this can be. The utility of a shiny 4k display is
weakened if your internet connection can't handle the bandwidth to fully take
advantage of it. Thanks to neural networks that can recreate high definition frames
from a low definition input, we could soon be streaming low definition streams over
our internet connection, while still enjoying the high definition glory that our
displays are capable of.
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10. The Future
Deep Learning use in film and broadcast has only begun to nibble at the edges of
what it will be used for in the future. I believe its future in the video industry is
particularly bright. However, as with all new technologies, deep learning is not
without a downside. As with deepfakes or face recognition misuse, there are valid
concerns of privacy and trust that arise from the rapid evolution of this technology.
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11. Thank You…