Convolutional neural networks (CNNs) have emerged as a preferred approach for medical image analysis. The dimensionality of images is a principal factor in CNN models, as they are designed to ...

On the analytical front, machine learning and deep learning methods have become increasingly prevalent. Random forest and ...

A research team has developed a novel deep learning framework that integrates 3D radiative transfer modeling (RTM) with a ...

We implement the neuromorphic radar system through a printed-circuit board (PCB) prototype and carry out simulations for the ...

Over the past decade, advancements in machine learning (ML) and deep learning (DL) have revolutionized segmentation accuracy.

Here, researchers from Beijing Institute of Nanoenergy and Nanosystems (Chinese Academy of Sciences) and Yonsei University present the latest progress in neuromorphic computing by integrating various ...

Scientists are seeking to decipher the role of non-coding DNA in the human genome, helped by a suite of ...

Stanford engineers have created new VR glasses that are thinner than a credit card and generate lifelike, mixed-reality holographic visuals.

A Fortran-based feed-forward neural network library. Whilst this library currently has a focus on 3D convolutional neural networks (CNNs), it can handle most standard hidden layer forms of neural ...