Artificial intelligence technology is able to break down a painting's visual attributes. Trained by data from online users, the deep convolutional neural network was accurately able to predict an individual's taste in art.
A new artificial intelligence convolutional neural network is 94.6% accurate at diagnosing real-time intraoperative brain tumors.
Combining neuroimaging data with deep convolutional neural networks, researchers were able to predict where people would direct their attention and gaze at images of natural scenes.
Researchers answer the questions of whether artificial intelligence is better at facial recognization than humans. The study found both humans and deep learning algorithms perform with similar levels of accuracy when identifying faces. However, when AI technology is combined with human intelligence, the accuracy attainment levels shot up and better results were achieved than when two facial examiners worked together.
A newly developed convolutional neural network learns more quickly and requires less image data sets than conventional networks.
