A key limitation of existing artificial intelligence (AI) systems is that they are unable to tackle tasks for which they have not been trained. In fact, even when they are retrained, the majority these systems are prone to 'catastrophic forgetting,' which essentially...
Researchers at TU Delft in the Netherlands have recently developed a convolutional neural network (CNN)-based model to reconstruct drawings that have deteriorated over time. In their study, published in Springer's Machine Vision and Applications, they specifically...
Adversarial audio attacks are small perturbations that are not perceivable by humans and are intentionally added to audio signals to impair the performance of machine learning (ML) models. These attacks raise serious concerns about the security of ML models, as they...
In recent years, researchers have proposed a wide variety of hardware implementations for feed-forward artificial neural networks. These implementations include three key components: a dot-product engine that can compute convolution and fully-connected layer...
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, such as walking, breathing or swimming.
A team of researchers at China University of Geosciences and Wuhan WXYZ Technologies in China has recently proposed a new machine learning-based technique to locate people's eyes in images of their faces. This technique, presented in a paper published in Elsevier's...
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 their advantages, so far, very few...
Advancements in robotics and artificial intelligence (AI) are enabling the development of artificial agents designed to assist humans in a variety of everyday settings. One of the many possible uses for these systems could be to escort humans or valuable goods that...
Over the past decade or so, advances in machine learning have paved the way for the development of increasingly advanced speech recognition tools. By analyzing audio files of human speech, these tools can learn to identify words and phrases in different languages,...
Accurately predicting the arrival times of buses is of key importance, particularly in hectic urban environments. Providing people with efficient and timely transportation can discourage them from using private vehicles, consequently reducing both fuel consumption and...