Method In this study, we developed a deep convolutional neural network (DCNN) for the localisation of the scleral spur; moreover, we introduced an information-rich segmentation approach for this ...

This study introduces a novel Convolutional Long Short-Term Memory (ConvLSTM) network for steel structure damage detection, aimed at enhancing the accuracy and reliability of structural health ...

Tomra Mining launched CONTAIN, a deep learning technology designed to improve the recovery of inclusion-type ores that ...

Applied Analytics professor Siddhartha Dalal discusses the impacts of applied technologies on real-life risk management.

Deep Learning Architectures. Deep learning architecture refers to the overall design and structure of the deep learning process. The architecture’s design principles determine how layers are connected ...

The article broadly covers the integration of deep learning techniques in the field of protein structure prediction, highlighting notable advances and comparing them to traditional computational ...

In a way, deep learning is how we humans learn new things. For instance, you might teach a toddler to recognize a bird by showing lots of pictures of all kinds of birds.

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

Understanding how cities grow is vital for shaping sustainable urban futures—but mapping the true extent of urban expansion remains a formidable technical hurdle. A new global study takes on this ...

CONTAIN™ represents the next breakthrough in AI-powered ore sorting from TOMRA Mining – a deep learning solution purpose-built to classify complex inclusion-type ores with unprecedented accuracy. By ...