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...
Computer Sciences
Using deep learning to localize human eyes in images
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...
Investigating the self-attention mechanism behind BERT-based architectures
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...
A deep learning approach to coordinate defensive escort teams
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...
A new approach to address food security issues after natural disasters
Researchers at Colorado State University (CSU) have developed an approximate dynamic programming approach to improve the food security of communities affected by natural disasters. Their work exploring methods to aid community recovery spans several papers. Their most...
Speech recognition using artificial neural networks and artificial bee colony optimization
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,...
Using artificial neural networks (ANNs) to predict bus arrival times
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...
A new approach to overcome multi-model forgetting in deep neural networks
In recent years, researchers have developed deep neural networks that can perform a variety of tasks, including visual recognition and natural language processing (NLP) tasks. Although many of these models achieved remarkable results, they typically only perform well...
A new approach to discover visual patterns in art collections
Researchers at UC Berkeley and Ecole des Ponts Paris Tech have recently developed a deep learning approach for discovering recurring visual patterns in art collections. Their paper, pre-published on arXiv, will be presented at CVPR 2019, a renowned computer vision...
Using machine learning to generate persuasive faces for ads
Researchers from the University of Pittsburgh have recently developed a conditional variational autoencoder that can produce unique faces for advertisements. Their study is grounded on their previous work, which explored automated methods of better understanding...