“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...

Last month, Nvidia announced a new platform called Maxine that uses AI to enhance the performance and functionality of video conferencing software. The software uses a neural network to create a ...

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.