12 citations · 18 across the 6 of their papers we have counts for
4 papers · 1 filter
Multi-level Feature Learning on Embedding Layer of Convolutional Autoencoders and Deep Inverse Feature Learning for Image Clustering
Behzad Ghazanfari, Fatemeh Afghah
This paper introduces Multi-Level feature learning alongside the Embedding layer of Convolutional Autoencoder (CAE-MLE) as a novel approach in deep clustering. We use agglomerative…
Piece-wise Matching Layer in Representation Learning for ECG Classification
Behzad Ghazanfari, Fatemeh Afghah, Sixian Zhang
This paper proposes piece-wise matching layer as a novel layer in representation learning methods for electrocardiogram (ECG) classification. Despite the remarkable performance of…
Deep Inverse Feature Learning: A Representation Learning of Error
Behzad Ghazanfari, Fatemeh Afghah
This paper introduces a novel perspective about error in machine learning and proposes inverse feature learning (IFL) as a representation learning approach that learns a set of hig…
Inverse Feature Learning: Feature learning based on Representation Learning of Error
Behzad Ghazanfari, Fatemeh Afghah, MohammadTaghi Hajiaghayi
This paper proposes inverse feature learning as a novel supervised feature learning technique that learns a set of high-level features for classification based on an error represen…