Robotics
To tackle different real-world tasks, robots should be able to handle and manipulate a variety of objects and materials, including paper. While roboticists have successfully improved the ability of humanoid robots or robotic ...
Electronics & Semiconductors
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 ...
Robotics
In recent years, roboticists and computer scientists have been developing a wide range of systems that can detect objects in their environment and navigate it accordingly. Most of these systems are based on machine learning ...
Computer Sciences
Event sensors, such as DVS event cameras and NeuTouch tactile sensors, are sophisticated bio-inspired devices that mimic event-driven communication mechanisms naturally occurring in the brain. In contrast with conventional ...
Robotics
While research in the field of robotics has led to significant advances over the past few years, there are still substantial differences in how humans and robots handle objects. In fact, even the most sophisticated robots ...
Robotics
In recent years, research teams worldwide have been using reinforcement learning (RL) to teach robots how to complete a variety of tasks. Training these algorithms, however, can be very challenging, as it also requires substantial ...
Robotics
Most humans can learn how to complete a given task by observing another person perform it just once. Robots that are programmed to learn by imitating humans, however, typically need to be trained on a series of human demonstrations ...
Machine learning & AI
Live 2-D animation is a fairly new and powerful form of communication that allows human performers to control cartoon characters in real time while interacting and improvising with other actors or members of an audience. ...
Machine learning & AI
Over the past few years, researchers have created a growing number of machine learning (ML)-based face recognition techniques, which could have numerous interesting applications, for instance, enhancing surveillance monitoring, ...
Computer Sciences
Researchers at Chongqing University in China have recently developed a cost-sensitive meta-learning classifier that can be used when the training data available is high-dimensional or limited. Their classifier, called SPFCNN-Miner, ...
