Mayur Rele is a cloud automation expert and cybersecurity leader that has a wide experience in overseeing global technology, cloud infrastructure, and security in healthcare, e-commerce, and technology companies. Mayur graduated with an M.S. in Computer and Telecommunications Engineering from Stevens Institute of Technology and is an active IEEE researcher and contributor.
Nowadays, people seem to take for granted how sophisticated and powerful computers have become. You can talk to your phones, and your Bluetooth speakers and they will respond with context-aware information; in certain cars, you can take your hands off the wheel and let yourself be carried down the road by electronics, and you can also share pictures and messages at the touch of a button anywhere around the world.
But one aspect where your devices are still very much in their infancy is that of computer 'vision'. While there are ever-better cameras in markets today, but in terms of understanding the world, these devices are quite dumb. While they can see with superb precision, they can't yet understand what they are seeing.
For example, if one shows a three-year-old child an image of a person standing next to an elephant, they would have no issues telling what they are seeing, but it would be extremely challenging for a computer to do the same.
The efficiency of convolutional nets in image recognition is one of the main reasons why the world has woken up to the effectiveness of deep learning. In a way, CNNs made deep learning famous. CNNs are powering significant advances in computer vision (CV), which has obvious applications for self-driving cars, robotics, security, drones, treatments, and medical diagnoses for the visually impaired.
Convolutional networks can also perform more profitable (and more banal), business-oriented tasks like optical character recognition (OCR) to digitize text and make natural-language processing possible on analog and hand-written documents, where the images are symbols to be transcribed.
CNNs are not limited to image recognition, however. They have been applied directly to text analytics. And they can be applied to sound when it is represented visually as a spectrogram, and graph data with graph convolutional networks.
Read More: https://www.wfmj.com/story/42306277/ai-expert-mayur-rele-gives-an-intuitive-explanation-of-convolutional-neural-networks
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Mayur Rele
AventuraMayur Rele has over 12 years of global experience in managing and evangelizing products in hi-tech for technology companies, startups, and hyper growth companies. Mayur's areas of expertise are IT strategy, business development, and cybersecurity. H...
