Electronic Design

Maximize Flexibility for AI at the Edge

Very few areas of industry will escape the influence of artificial intelligence, with many applications involving security ...
The New York Times

Tesla’s Model S, Soon to Be History, Changed the Auto Industry

The company’s chief executive, Elon Musk, said this week that it would stop making the car, an electric pioneer in 2012, as well as the Model X. By Neal E. Boudette Thirteen years ago, Mike Ramsey, an ...
GitHub

ResNet-50 Image Classification

This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...
GitHub

Blood Group Prediction using Fingerprint images (ResNet-18)

This project provides a non-invasive system to predict a person’s ABO/Rh blood group from their fingerprint image using deep learning. The solution combines advanced CNN modeling, non-invasive data ...
Hacker

Fine-Tuning ResNet-18 with TensorFlow Model Garden for CIFAR-10 Classification

This tutorial walks you through fine-tuning a ResNet-18 model from TensorFlow’s Model Garden for classifying images in the CIFAR-10 dataset. You’ll learn how to set up the environment, configure the ...
IEEE

Classification Based Deep Learning Models for Lung Cancer and Disease Using Medical Images

Abstract: The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a novel deep convolutional neural network ...
Frontiers

Application of deep learning based on convolutional neural network model in multimodal ultrasound diagnosis of unexplained cervical lymph node enlargement

This study retrospectively analyzed the multimodal ultrasound features and clinical characteristics of 586 patients with unexplained cervical lymphadenopathy who were treated at three hospitals ...
IEEE

The Impact of Integrating Shallow and Deep Information on Knowledge Distillation

Abstract: Knowledge distillation is a key technique for compressing neural networks, leveraging insights from a large teacher model to enhance the generalization capability of a smaller student model.