Category: Uncategorized

AI: Smart CCTV Features Facial Recognition Voice Recognition & Security …
I returned from work like every other day… first thing, go to the kitchen to check the messages on the house phone… believed or not it is very useful… but that is for another post… Suddenly I heard a voice telling me that my dog was found in the middle of the street on the verge to be smashed by a car. What! I called her back. I went for my dog to the specific location she chose … There is another long story about the details… The main point is why my dog was on the streets. Still a mystery! If I have had my surveillance camera I would have known what had happen… Some UPS packages have been stolen from houses making big news; some owners have a surveillance camera and had their packages back thanks to their surveillance camera… What are we waiting for? The recognition of faces, situations, unexpected objects… in our cities, can be identified and taking care of in a better, faster and efficient way than ever before. If you are concerned about your privacy then believe me a machine does not care, and the cameras are not programmed to care. Let’s be efficient.

(Source: https://www.youtube.com/)
by perlajulieta

Deep Learning for Text Understanding from Scratch

LET THE MACHINE LEARN EVERYTHING! The network is designed as a traditional deep ConvNet, with successions of convolutional and pooling layers, finishing with 2 fully connected layers. The succession of convolutions makes it possible to learn very diverse sets of features, by learning convolutions of convolutions of convolutions (as if we looked at, for example, the blurred embossed image of the edges of an image, but with the actual operation being learned by the system). We learn to read like that! We arrange images in our brain, we learn the characters and associate them with sounds. We practice convolutions of convolutions until we get 100% accuracy. Babies go by images, and then we rhyme with them or say words and little phrases with the images. We keep doing that over time until they train their brain to evaluate images of entire sentences; we still go on for the ones who train themselves to fast reading.

Deep Learning for Text Understanding from Scratch

by perlajulieta

LET THE MACHINE LEARN EVERYTHING! The network is designed as a traditional deep ConvNet, with successions of convolutional and pooling layers, finishing with 2 fully connected layers. The succession of convolutions makes it possible to learn very diverse sets of features, by learning convolutions of convolutions of convolutions (as if we looked at, for example, the blurred embossed image of the edges of an image, but with the actual operation being learned by the system). We learn to read like that! We arrange images in our brain, we learn the characters and associate them with sounds. We practice convolutions of convolutions until we get 100% accuracy. Babies go by images, and then we rhyme with them or say words and little phrases with the images. We keep doing that over time until they train their brain to evaluate images of entire sentences; we still go on for the ones who train themselves to fast reading. Learning for Text Understanding from Scratch

Deep Learning for Text Understanding from Scratch.

by perlajulieta

Flight of the bumblebee
“Flight of the Bumblebee” is an orchestral interlude written by Nikolai Rimsky-Korsakov for his opera The Tale of Tsar Saltan, composed in 1899–1900. The piece closes Act III, Tableau 1, during which the magic Swan-Bird changes Prince Gvidon Saltanovich (the Tsar’s son) into an insect so that he can fly away to visit his father (who does not know that he is alive). Although in the opera the Swan-Bird sings during the first part of the “Flight”, her vocal line is melodically uninvolved and easily omitted; this feature, combined with the fact that the number decisively closes the scene, made easy extraction as an orchestral concerto piece possible

(Source: https://www.youtube.com/)
by perlajulieta