A Hybrid convolutional neural network for sketch recognition

•We propose a novel Hybrid CNN architecture to address the problem of sketch recognition.•S-Net extracts shape features, which is invariant for sketch rotation and transformation.•Hybrid CNN achieves state-of-the-art on sketch classification and sketch-based image retrieval tasks.•The classification accuracy is 84.42% and 82.74% on TU-Berlin and SketchX datasets, respectively.•The MAP of SBIR is 57.4% and 28.74% on SketchX and Flickr15K-Large datasets, respectively.