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 ...

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

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

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.

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 ...

Deep learning is an extension of some of the concepts originating from machine learning, so for that reason, let’s take a minute to explain what machine learning is. Put simply, machine learning is a ...

New deep learning algorithm predicts effects of rare genetic variants. ... information on the possible effects that the respective variant can have on cellular processes or on the protein structure.

Data scalability: Deep learning models are also known to perform increasingly well as the volume of data grows. This is in ...