The SMPTE timecode standard has served us well for almost half a century. But the equipment it was designed for is history, and soon it will be too. The industry needs a replacement.
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Deep learning technology is more common than one might think. This technology is used to identify objects in images, texts or audio, achieving results that were not possible before. This article will examine how deep learning is revolutionizing sports production to enable low-cost, fully automated production for semi-professional and amateur sports broadcasts.
The Satellite Interference Reduction Group announced that it is expanding its reach to encompass all types of innovation within the satellite communications industry. As part of that expansion, it has changed its name to Satcoms Innovation Group (SIG).
Looking to take advantage of distribution and cost benefits, many broadcasters have expressed an interest in migrating to full IP infrastructures. However, if you’ve got a full complement of baseband equipment and workflows that your team is familiar with, it might not be practical to attempt a complete overhaul in a facility.
Most novice videographers can plug a microphone into a mic jack and get a reasonably good audio signal. However, at times, many get noise, distortion or an unusably low audio level. That is usually caused by mismatch in audio connection types.
With a sharp focus on IP-based operations and the impact they have on a variety of broadcast operations and workflows, broadcasters are operating in one of the most dramatic periods of technological change that the international broadcast industry has ever experienced.
IP offers the hope of cutting the cost of production if you know how to move the signal around using inexpensive equipment.
At the SMPTE 2018 Technical conference, Dr. Takeshi Shimizu, Media Links, presents a revolutionary new theory about constructing a three-stage Clos network with non-blocking multicast capability.
