Researchers at the Polish-Japanese Academy of Information Technology and Warsaw University of Technology have developed a deep alignment network (DAN) model to classify and visualize emotions. Their method was found to outperform state-of-the-art emotion...
Every day, millions of articles are published on social media and other platforms, receiving a vast amounts of clicks and shares from users navigating the web. Many of these articles contain useful information that, if extracted, could be used to compile knowledge...
A team of researchers at North Carolina State University has recently carried out an empirical analysis of the executable status of Python code snippets shared on GitHub. Their study, pre-published on arXiv, also presents Gistable, a new database of executable Python...
Humans have the innate ability to predict the effect of collisions, merely using their common sense. In many cases, humans can even predict the results of similar collisions in situations in which mass, friction, or other factors vary. Could machines also attain a...
Over the past few years, classical convolutional neural networks (cCNNs) have led to remarkable advances in computer vision. Many of these algorithms can now categorize objects in good quality images with high accuracy.
Researchers at Orange Labs and Normandie University have developed a novel deep neural model for audiovisual emotion recognition that performs well with small training sets. Their study, which was pre-published on arXiv, follows a philosophy of simplicity,...
Researchers at Laboratório de Computação de Alto Desempenho (LCAD) of Universidade Federal do Espírito Santo (UFES), in Brazil, have devised a novel strategy for correcting imperfections in occupancy grid maps by correcting invalid occupancy probabilities of map cells...
Researchers at the State University of New York in Korea have recently explored new ways to detect both machine and human-created fake images of faces. In their paper, published in ACM Digital Library, the researchers used ensemble methods to detect images created by...
Researchers at Shenzhen University have recently devised a method to detect images generated by deep neural networks. Their study, pre-published on arXiv, identified a set of features to capture color image statistics that can detect images generated using current...
A team of researchers at Cyxtera Technologies has recently proposed a neural network-based method for identifying malicious use of web certificates. Their approach, outlined in a paper published in ACM Digital Library, uses the content of transport layer security...