BIOENGINEER

LiteSGNet Enables Ultra-Lightweight Signal Modulation Classification for Edge Spectrum Sensing

Researchers developed LiteSGNet, an ultra-lightweight automatic modulation classification network that achieves up to 66.11% ...
BIOENGINEER

Deep Learning Model Reaches 98.39% Accuracy in Cotton Leaf Disease Classification

A hybrid ConvNeXt and Random Walk Grey Wolf Optimizer framework classified six categories of cotton leaf conditions with ...
Semiconductor Engineering

Using Deep Learning ADC For Defect Classification For Automatic Defect Inspection

In traditional semiconductor packaging, manual defect review after automated optical inspection (AOI) is an arduous task for operators and engineers, involving review of both good and bad die. It is ...
2 Minute Medicine

Deep learning model demonstrates potential to generate an interpretable brain health biomarker from sleep electroencephalography

Ganglberger and colleagues assessed a deep learning model’s ability to derive brain health scores from electroencephalography ...

3 Essential Books for Learning Deep Learning with Keras

Introduction A few years ago, when I was tasked with an in-house PoC for image classification, I took sample code for transfer learning and ran it almost as-is. The training ran. The accuracy stopped ...
GitHub

A Hybrid Deep Learning Architecture for an Intelligent Library Search System with NLP

A Hybrid Deep Learning Architecture for an Intelligent Library Search System with NLP - RiteshPawar05/Smart-Library-Chatbot ...

What is "Transfer Learning" that achieves high accuracy with little data?

In deep learning, a vast amount of training data is usually required. However, in practice, we often hit a wall where we ...