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.
Hybrid systems are systems that exhibit both continuous and discrete dynamic behavior, allowing more flexibility in modeling dynamic phenomena. Hybrid systems modeling languages are widely used for the development of cyber-physical systems, in which control software...
Researchers at MIT's Computer Science and Artificial Intelligence Laboratory have recently developed a chance-constrained motion planning system that can be applied to high degree-of-freedom (DOF) robots under motion uncertainty and in cases of imperfect state...
Researchers at Pennsylvania State University, MIT and Georgia Institute of Technology have recently developed a conceptual framework to model the human-robot trust phenomenon. Their framework, outlined in a paper published on ACM Digital Library, uses computational...
Researchers at Arizona State University (ASU) have recently developed a new method of detecting unusual activity in traffic surveillance videos, which is based on an adaptive anomaly detection (AAD) framework. Their method, outlined in a paper pre-published on arXiv,...
Researchers at Shree Devi Institute of Technology, in India, have recently carried out a study investigating the use of artificial intelligence (AI) to communicate with deceased loved ones. Like in the chilling sci-fi fantasy foreshadowed by popular television series...
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...
Researchers at Sapientia University in Romania and Université de Lyon have recently carried out a performance evaluation of unrestricted mouse usage for impostor detection. Their findings, pre-published on arXiv, suggest that drag-and-drop mouse actions are the most...
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,...