Semiconductor Engineering

Convolutional Neural Network (CNN)

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 ...
Semiconductor Engineering

Convolutional Neural Network With INT4 Optimization

INT8 provides better performance with comparable precision than floating point for AI inference. But when INT8 is unable to meet the desired performance with limited resources, INT4 optimization is ...
Electronic Design

A Neural-Network-Based Approach to Smarter DPD Engines

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

Ultra-short-term PV forecasting based on convolutional neural network, long short-term memory

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 ...
Hosted on MSN

Build A Deep Neural Network From Scratch In Python — No Tensorflow!

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...
Hosted on MSN

Neural Network python from scratch | MultiClass Classification with Softmax

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 ...
JSTOR Daily

Wave Monitoring Based on Improved Convolution Neural Network

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 ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

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 ...