Researchers at Oxford University have recently tried to recreate human thinking patterns in machines, using a language guided imagination (LGI) network. Their method, outlined in a paper pre-published on arXiv, could inform the development of artificial intelligence...
Machine learning & AI
A CNN-based method to detect end-to-end multiplayer violence
Researchers at China University of Petroleum (CUP), in Beijing, have recently developed a new method for multiplayer violence detection based on deep 3-D convolutional neural networks (CNNs). Their method was presented in a paper published in ICNCC 2018: Proceedings...
A new method for understanding ancient coin images
Two researchers at the University of St. Andrews, in Scotland, have recently developed a new machine learning-based method for understanding images of ancient coins. Their study, pre-published on arXiv applies computer vision and machine learning to ancient numismatics.
Object detection in 4K and 8K video using GPUs
Researchers at Carnegie Mellon University have recently developed a new model that enables fast and accurate object detection in high-resolution 4K and 8K video footage using GPUs. Their attention pipeline method carries out a two-stage evaluation of every image or...
Emotion recognition based on paralinguistic information
Researchers at the University of Texas at Arlington have recently explored the use of machine learning for emotion recognition based solely on paralinguistic information. Paralinguistics are aspects of spoken communication that do not involve words, such as pitch,...
A new dynamic ensemble active learning method based on a non-stationary bandit
Researchers at the University of Edinburgh, University College London (UCL) and Nara Institute of Science and Technology have developed a new ensemble active learning approach based on a non-stationary multi-armed bandit and an expert advice algorithm. Their method,...
Analyzing spoken language and 3-D facial expressions to measure depression severity
Researchers at Stanford have recently explored the use of machine learning to measure the severity of depressive symptoms by analyzing people's spoken language and 3-D facial expressions. Their multi-model method, outlined in a paper pre-published on arXiv, achieved...
CruzAffect: a feature-rich approach to characterize happiness
A team of researchers at UC Santa Cruz have recently developed a new machine learning approach to characterize happiness, called CruzAffect. Their approach, presented in a paper pre-published on arXiv, can be applied to different models for affective content...