InceptionV4

A high-performance deep convolutional neural network that integrates residual connections with the Inception architecture to accelerate training and boost accuracy.

InceptionV4 represents a significant evolution in computer vision, merging the multi-scale feature extraction of the Inception family with the simplified architecture of ResNet. Developed by Google researchers (Christian Szegedy et al.), it achieves a top-5 error rate of 3.08% on the ILSVRC 2012 classification task. By utilizing a uniform structure for each Inception block and removing unnecessary architectural complexities, the model optimizes computational efficiency. This design allows for deeper networks that are easier to train, providing a robust foundation for complex image recognition and object detection tasks.

https://arxiv.org/abs/1602.07261