| 2021 | DocEng | Text line extraction using deep learning and minimal sub seams. | Adi Azran, Alon Schclar, Raid Saabni |
| 2020 | IJCCI | A Diffusion Dimensionality Reduction Approach to Background Subtraction in Video Sequences. | Dina Dushnik, Alon Schclar, Amir Averbuch, Raid Saabni |
| 2020 | ICPRAM | A Manifold Learning Framework for the Detection of Cardiac Disorders in Acoustic Signals. | Keren Hochman, Amir Averbuch, Alon Schclar, Raid Saabni |
| 2019 | IJCCI | Unsupervised Detection of Sub-pixel Objects in Hyper-spectral Images via Diffusion Bases. | Alon Schclar, Amir Averbuch |
| 2017 | IJCCI | Unsupervised Segmentation of Hyper-spectral Images via Diffusion Bases. | Alon Schclar, Amir Averbuch |
| 2017 | IJCCI | A Diffusion Approach to Unsupervised Segmentation of Hyper-Spectral Images. | Alon Schclar, Amir Averbuch |
| 2015 | IJCCI | Diffusion Bases Dimensionality Reduction. | Alon Schclar, Amir Averbuch |
| 2013 | CHI | MATE: a mobile analysis tool for usability experts. | Talya Porat, Alon Schclar, Bracha Shapira |
| 2012 | IJCCI | Diffusion Ensemble Classifiers. | Alon Schclar, Lior Rokach, Amir Amit |
| 2010 | GRC | k-Anonymized Reducts. | Lior Rokach, Alon Schclar |
| 2009 | RecSys | Ensemble methods for improving the performance of neighborhood-based collaborative filtering. | Alon Schclar, Alexander Tsikinovsky, Lior Rokach, Amnon Meisels, Liat Antwarg |
| 2002 | ICASSP | Deblocking of block-DCT compressed images using deblocking frames of variable size. | Alon Schclar, Amir Averbuch, David L. Donoho |