Classifying galaxies in the Galaxy10 DECals dataset using Inception and Residual CNNs
Researchers have evaluated the performance of ResNet101 and InceptionV4 convolutional neural networks for classifying galaxy images. Both models achieved approximately 90% accuracy on the Galaxy10 DECals dataset, demonstrating their suitability for future astronomical surveys. The study found ResNet101 to be slightly superior to InceptionV4 in terms of performance metrics. AI
IMPACT Demonstrates the effectiveness of existing CNN architectures for astronomical image classification, potentially streamlining future research.