Description
Inception-v4 is a convolutional neural network architecture that builds on previous iterations of the Inception family by simplifying the architecture and using more inception modules than Inception-v3.
Papers Using This Method
Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution2025-01-12DeepGI: An Automated Approach for Gastrointestinal Tract Segmentation in MRI Scans2024-01-27Semi-supervised Vision Transformers at Scale2022-08-11Ensemble CNN models for Covid-19 Recognition and Severity Perdition From 3D CT-scan2022-06-29Danish Fungi 2020 -- Not Just Another Image Recognition Dataset2021-03-18Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT scans2020-09-10The Effects of Approximate Multiplication on Convolutional Neural Networks2020-07-20A Deep Learning based Wearable Healthcare IoT Device for AI-enabled Hearing Assistance Automation2020-05-16Effective, Fast, and Memory-Efficient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification2018-11-29Deep neural network ensemble by data augmentation and bagging for skin lesion classification2018-07-15Improved Inception-Residual Convolutional Neural Network for Object Recognition2017-12-28RECOD Titans at ISIC Challenge 20172017-03-14Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning2016-02-23