Diabetic retinopathy identification using parallel convolutional neural network based feature extractor and ELM classifier.

•Diabetic retinopathy (DR) detection from Fundus Images has been proposed.•Parallel CNN with fewer parameters and layers for distinctive feature extraction.•Extreme Learning Machine (ELM) technique was utilized for the DR classification.•The model demonstrated robustness for different types of datasets.•Accuracy upto 97.27 % was achieved and outscored state-of-the-art models.