Past research has identified student engagement, or the extent to which students participate and are involved in classroom activities, as a crucial factor determining both the quality of education programs and the academic performance of individual students. As a...
Over the past few decades, people around the world have been dealing with a vast variety of environmental threats. In Australia, these include risks associated with the deterioration and destruction of aquatic plants, animals and other organisms that inhabit...
In recent years, countless computer scientists worldwide have been developing deep neural network-based models that can predict people's emotions based on their facial expressions. Most of the models developed so far, however, merely detect primary emotional states...
Micro-sized robots could bring a new wave of innovation in the medical field by allowing doctors to access specific regions inside the human body without the need for highly invasive procedures. Among other things, these tiny robots could be used to carry drugs, genes...
Researchers at Rensselaer Polytechnic Institute and IBM Research in New York have recently created pFoodReQ, a system that can recommend recipes tailored around the preferences and dietary needs of individual users. This system is outlined in a paper pre-published on...
Researchers at Harvard University have recently devised a system based on Wi-Fi sensing that could enhance the collaboration between robots operating in unmapped environments. This system, presented in a paper pre-published on arXiv, can essentially emulate antenna...
Robots are rapidly making their way into a variety of settings, including industrial and manufacturing facilities. So far, they have shown great potential for speeding up and automating a number of manufacturing processes by substituting or assisting human workers on...
Machine learning techniques are designed to mathematically emulate the functions and structure of neurons and neural networks in the brain. However, biological neurons are very complex, which makes artificially replicating them particularly challenging.
Over the past decade or so, deep neural networks have achieved very promising results on a variety of tasks, including image recognition tasks. Despite their advantages, these networks are very complex and sophisticated, which makes interpreting what they learned and...
Two researchers at Duke University have recently devised a useful approach to examine how essential certain variables are for increasing the reliability/accuracy of predictive models. Their paper, published in Nature Machine Intelligence, could ultimately aid the...