Facebook has revolutionized the world of social networking. The founders of the social networking site started it on their premises while studying at Harvard, and what started out as a simple thing has grown exponentially. They were recently on the news for the acquisition of the WhatsApp messaging service, with speculation about the direction they are taking. They recently invented software that they claim can match faces better than humans. According to research, a person can assign photos of two unknown faces to 97.53 percent. This is independent of the lighting situation or whether the people in the pictures are facing the camera.
We write early about a dangerous social networking site, but Facebook and its competitors have been actively working on the software called deep learning. It is an artificial intelligence software that uses a complex method of matching faces. The software uses a network of neurons that help them slowly recognize patterns in large data pools. The new software achieves 97.25 percent in the recognition of faces, which is a significant improvement over the previous software for artificial intelligence. According to Facebook’s Artificial Intelligence researchers, it is approaching human performance. The margin of error has been reduced by more than a quarter compared to previous software.
The software uses a 3-dimensional model that rotates faces so that even when they look away, they face the camera. It does what researchers call facial examination as facial recognition. Face verification detects whether two images show the same face, while face recognition software places faces in faces. The two techniques can be combined, which will improve Facebook’s ability to recognize whether two faces are the same and give them names. Combining these techniques could be helpful in suggesting which photos to put photos on, but this technology can also be dangerous.
The DeepFace project, which Facebook calls it, is at least in the preliminary stages of research. Facebook recently published a paper on the project aimed at the IEEE technology conference in June. The goal of the publication is to get feedback from other members of the technological research community. The software pioneers are Yaniv Taigman together with Ming Yang and another colleague Marc’Aurelio Ranzato. A professor Lior Wolf from a university in Israel was also involved in the project development. Taigman has spoken a lot about the project in public circles. We at signal jammer hope that this project will go in a positive direction.
The DeepFace project works in two phases. In the first phase, the software virtually changes the angle of view. The correction is such that the picture faces forward in the picture. The software uses a three-dimensional model of a typical average front surface. In the next stage, the neural network comes into play. It calculates a numerical description of the face. At this stage, it compares the numerical data collected from the two images. If there are enough similarities in the data, the software decides that the two images have the same face. If you don’t trust this modern technology, we recommend that you choose portable or stationary jammers that we offer in our store.