A team of researchers at the University of North Carolina at Chapel Hill and the University of Maryland at College Park has recently developed a new deep learning model that can identify people's emotions based on their walking styles. Their approach, outlined in a...
Researchers at the University of Waterloo, Canada, have recently developed a system for generating song lyrics that match the style of particular music artists. Their approach, outlined in a paper pre-published on arXiv, uses a variational autoencoder (VAE) with...
In years to come, self-driving vehicles could gradually become a popular means of transportation. Before this can happen, however, researchers will need to develop tools that ensure that these vehicles are safe and can efficiently navigate in human-populated...
Researchers at Leiden University and the National University of Defense Technology (NUDT), in China, have recently developed a new approach for image-text matching, called CycleMatch. Their approach, presented in a paper published in Elsevier's Pattern Recognition...
Detecting and analyzing cracks in man-made structures is an important task that can help to ensure that buildings are safe and well-maintained. As employing human workers to inspect buildings regularly can be very expensive, researchers have been trying to develop...
A team of researchers at the University of Memphis has recently developed a low-cost and portable traffic monitoring system (TMS) called DeepWiTraffic. This new system, presented in a paper pre-published on arXiv, combines Wi-Fi devices and deep learning.
Advances in the field of AI have enabled the development of tools that can understand a variety of languages and communicate with humans. However, there are still aspects of human communication that AI systems struggle with, one of which is humor.
Researchers at Clova AI Research, NAVER and LINE, have recently proposed a new framework called AQM+ that allows dialog systems to generate context-relevant questions and answers. Their model, outlined in a paper pre-published on arXiv, will be presented at the 7th...
Over the past decade or so, deep-learning approaches have become increasingly efficient in processing static data such as images. However, these techniques have been found to be somewhat less effective in analyzing temporal data, such as videos, human speech and other...
A team of researchers at Technion and the University of Haifa have developed a new computer vision approach for solving archaeological puzzles. In their paper, pre-published on arXiv, they introduce a general algorithm that can automatically reassemble fragments of...