Robotics
As robots are gradually introduced into various real-world environments, developers and roboticists will need to ensure that they can safely operate around humans. In recent years, they have introduced various approaches ...
Computer Sciences
Most computer systems are designed to store and manipulate information, such as documents, images, audio files and other data. While conventional computers are programmed to perform specific operations on structured data, ...
Computer Sciences
BERT, a transformer-based model characterized by a unique self-attention mechanism, has so far proved to be a valid alternative to recurrent neural networks (RNNs) in tackling natural language processing (NLP) tasks. Despite ...
Energy & Green Tech
The batteries used to power electric vehicles have several key characterizing parameters, including voltage, temperature, and state of change (SOC). As battery faults are associated with abnormal fluctuations in these parameters, ...
Machine learning & AI
Researchers at Shanghai University have recently developed a new approach based on recurrent neural networks (RNNs) to predict scene graphs from images. Their approach includes a model made up of two attention-based RNNs, ...
Computer Sciences
A team of researchers at Universite du Quebec a Montreal and Vietnam National University Ho Chi Minh (VNU-HCM) have recently developed an approach for machine transliteration based on recurrent neural networks (RNNs). Transliteration ...
Computer Sciences
Central pattern generators (CPGs) are biological neural circuits that can produce coordinated rhythmic outputs without requiring rhythmic inputs. CPGs are responsible for most rhythmic motions observed in living organisms, ...
Computer Sciences
Researchers at Beijing Institute of Technology (BIT) have recently developed a new method to detect false data injection (FDI) attacks on critical infrastructure such as power grids. Their solution, outlined in a paper presented ...
Computer Sciences
Researchers at Taif University, Birzeit University and RMIT University have developed a new approach for software fault prediction (SFP), which addresses some of the limitations of existing machine learning SFP techniques. ...
Computer Sciences
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.
