Machine learning & AI

A method to reduce the number of neurons in recurrent neural networks

A team of researchers at Queen's University, in Canada, have recently proposed a new method to downsize random recurrent neural networks (rRNN), a class of artificial neural networks that is often used to make predictions ...

Machine learning & AI

A hierarchical RNN-based model to predict scene graphs for images

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, ...

Engineering

Teaching self-driving cars to predict pedestrian movement

By zeroing in on humans' gait, body symmetry and foot placement, University of Michigan researchers are teaching self-driving cars to recognize and predict pedestrian movements with greater precision than current technologies.

Computer Sciences

A new approach for low-resource machine transliteration using RNNs

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

A new method to detect false data injection (FDI) attacks

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

A new approach for software fault prediction using feature selection

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

Computer vision in the dark using recurrent CNNs

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.

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