Nuacht

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...
Cellular electron cryotomography (CryoET) is the dominant technique for studying the structure of interacting, dynamic complexes in their native cellular environment at nanometer resolution. While ...
“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 ...
Convolutional Neural Networks (CNN) are mainly used for image recognition. The fact that the input is assumed to be an image enables an architecture to be created such that certain properties can be ...
A Convolutional Neural Network (CNN) is a form of artificial intelligence that plays a key role in the AI ecosytem due to its ability to analyze and understand visual data. The need to decipher and ...
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 ...
Journal of Coastal Research, Special Issue No. 94: Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development (SUMMER 2019), pp. 186-190 (5 pages) As human’s ...
Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...