While many automotive companies are now invested in the development of self-driving cars, the vehicles created so far have not yet attained the safety levels necessary for them to be deployed on a large-scale. For this to happen, the vehicles will need to be able to...
Over the past few decades, the performance of machine learning models on various real-world tasks has improved significantly. Training and implementing most of these models, however, still requires vast amounts of energy and computational power.
Deep-learning models have proven to be highly valuable tools for making predictions and solving real-world tasks that involve the analysis of data. Despite their advantages, before they are deployed in real software and devices such as cell phones, these models...
In recent years, deep learning techniques have achieved remarkable results in numerous language and image-processing tasks. This includes visual speech recognition (VSR), which entails identifying the content of speech solely by analyzing a speaker's lip movements.
In recent years, deep learning techniques have proved to be highly valuable for tackling countless research and real-world problems. Researchers at Feedzai, a financial data science company based in Portugal, have demonstrated the potential of deep learning for the...
Researchers at the Electronics and Telecommunications Research Institute (ETRI) in Korea have recently developed a deep learning-based model that could help to produce engaging nonverbal social behaviors, such as hugging or shaking someone's hand, in robots. Their...
Advances in the field of machine learning have recently enabled the development of computational tools that can create convincing but artificially produced texts, also known as deepfake texts. While the automatic creation of texts could have some interesting...
Robots that can automatically recognize and track specific odors could have a wide range of valuable applications. For instance, they could help to identify the sources of harmful chemical substances in the air after hazardous accidents at power plants, explosions, or...
Recent advancements in the field of machine learning (ML) have greatly improved the quality of automatic translation tools. At present, these tools are primarily used to translate basic sentences, as well as short texts or unofficial documents.
A team of researchers from University of Illinois at Urbana-Champaign and Stanford University led by Prof. Katie Driggs-Campbell, have recently developed a new deep reinforcement learning-based method that could improve the ability of mobile robots to safely navigate...