An Image Encryption System by Cellular Automata with Memory. - Farhad Maleki; Ali Mohades; S. Mehdi Hashemi; Mohammad E. Shiri (ARES, 2008)

A CA Randomizers Based on parallel CAs with Balanced Rules. - Farhad Maleki; Ali Mohades; Mohammad E. Shiri; Afsane Bijari (ICCS, 2010)

Sample Size and Reproducibility of Gene Set Analysis. - Farhad Maleki; Katie L. Ovens; Ian McQuillan; Anthony J. Kusalik (BIBM, 2018)

Gene Set Databases: A Fountain of Knowledge or a Siren Call? - Farhad Maleki; Katie L. Ovens; Ian McQuillan; Elham Rezaei; Alan M. Rosenberg; Anthony J. Kusalik (BCB, 2019)

Gene Set Overlap: An Impediment to Achieving High Specificity in Over-representation Analysis. - Farhad Maleki; Anthony J. Kusalik (BIOINFORMATICS, 2019)

Method Choice in Gene Set Analysis Has Important Consequences for Analysis Outcome. - Farhad Maleki; Katie L. Ovens; Elham Rezaei; Alan M. Rosenberg; Anthony J. Kusalik (BIOINFORMATICS, 2019)

Crop Lodging Prediction From UAV-Acquired Images of Wheat and Canola Using a DCNN Augmented With Handcrafted Texture Features. - Sara Mardanisamani; Farhad Maleki; Sara Hosseinzadeh Kassani; Sajith Rajapaksa; Hema Sudhakar Duddu; Menglu Wang 001; Steve Shirtliffe; Seungbum Ryu; Anique Josuttes; Ti Zhang; Sally Vail; Curtis Pozniak; et al. (CVPR Workshops, 2019)

Measuring consistency among gene set analysis methods: A systematic study. - Farhad Maleki; Katie L. Ovens; Daniel J. Hogan; Elham Rezaei; Alan M. Rosenberg; Anthony J. Kusalik (J. Bioinform. Comput. Biol., 2019)

A Deep Learning-Based Pipeline for Celiac Disease Diagnosis Using Histopathological Images. - Farhad Maleki; Kevin Cote; Keyhan Najafian; Katie L. Ovens; Yan Miao; Rita Zakarian; Caroline Reinhold; Reza Forghani; Peter Savadjiev; Zu-hua Gao (CAIP (1), 2021)

A Semi-self-supervised Learning Approach for Wheat Head Detection using Extremely Small Number of Labeled Samples. - Keyhan Najafian; Alireza Ghanbari; Ian Stavness; Lingling Jin; Gholam Hassan Shirdel; Farhad Maleki (ICCVW, 2021)

Juxtapose: a gene-embedding approach for comparing co-expression networks. - Katie L. Ovens; Farhad Maleki; B. Frank Eames; Ian McQuillan (BMC Bioinform., 2021)

Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? - A Case Study using Dual Energy CT Data. - Andreas K. Maier; Seung Hee Yang; Farhad Maleki; Nikesh Muthukrishnan; Reza Forghani (CoRR, 2021)

Offer Proprietary Algorithms Still Protection of Intellectual Property in the Age of Machine Learning? - A Case Study Using Dual Energy CT Data. - Andreas K. Maier; Seung Hee Yang; Farhad Maleki; Nikesh Muthukrishnan; Reza Forghani (Bildverarbeitung für die Medizin, 2022)

Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls. - Farhad Maleki; Katie L. Ovens; Rajiv Gupta; Caroline Reinhold; Alan Spatz; Reza Forghani (CoRR, 2022)

Deep Learning-Based Hierarchical Delineation of Kidneys, Tumors, and Cysts in CT Images. - Andrew Heschl; Hosein Beheshtifard; Phuong Thao Nguyen; Tapotosh Ghosh; Katie L. Ovens; Farhad Maleki (KiTS@MICCAI, 2023)

Beyond Annotations: Efficient Wheat Head Segmentation Using L-Systems, Game Engines, and Student-Teacher Models. - Hosein Beheshtifard; Elijah Mickelson; Keyhan Najafian; Farhad Maleki (ECCV Workshops (3), 2024)

SynthSet: Generative Diffusion Model for Semantic Segmentation in Precision Agriculture. - Andrew Heschl; Mauricio Murillo; Keyhan Najafian; Farhad Maleki (ECCV Workshops (3), 2024)

Discovering Knowledge Embedded in Gene Set Databases: A Mathematical Modelling Approach. - Katie L. Ovens; Ebunoluwa Makinde; Samuel Horovatin; Elham Rezaei; Alan M. Rosenberg; Lingling Jin; Ian McQuillan; Anthony J. Kusalik; Farhad Maleki (ICCBB, 2024)

RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models. - Farhad Maleki; Linda Moy; Reza Forghani; Tapotosh Ghosh; Katie L. Ovens; Steve Langer; Pouria Rouzrokh; Bardia Khosravi; Ali Ganjizadeh; Daniel I. Warren; Roxana Daneshjou; Mana Moassefi; et al. (CoRR, 2024)

Modified CycleGAN for the synthesization of samples for wheat head segmentation. - Jaden Myers; Keyhan Najafian; Farhad Maleki; Katie L. Ovens (CoRR, 2024)

Automatic segmentation of Organs at Risk in Head and Neck cancer patients from CT and MRI scans. - Sébastien Quetin; Andrew Heschl; Mauricio Murillo; Rohit Murali; Shirin A. Enger; Farhad Maleki (CoRR, 2024)

DVOS: Self-Supervised Dense-Pattern Video Object Segmentation. - Keyhan Najafian; Farhad Maleki; Ian Stavness; Lingling Jin (CoRR, 2024)

Semi-Self-Supervised Domain Adaptation: Developing Deep Learning Models with Limited Annotated Data for Wheat Head Segmentation. - Alireza Ghanbari; Gholam Hassan Shirdel; Farhad Maleki (Algorithms, 2024)

Efficient Wheat Head Segmentation with Minimal Annotation: A Generative Approach. - Jaden Myers; Keyhan Najafian; Farhad Maleki; Katie L. Ovens (J. Imaging, 2024)

Agri-FM+: A Self-Supervised Foundation Model for Agricultural Vision. - Md Jaber Al Nahian; Tapotosh Ghosh; Farnaz Sheikhi; Farhad Maleki (CVPR Workshops, 2025)

A Semi-Self-Supervised Approach for Dense-Pattern Video Object Segmentation. - Keyhan Najafian; Farhad Maleki; Lingling Jin; Ian Stavness (CVPR Workshops, 2025)

Should we pre-train a decoder in contrastive learning for dense prediction tasks? - Sébastien Quetin; Tapotosh Ghosh; Farhad Maleki (CoRR, 2025)

From Semantic To Instance: A Semi-Self-Supervised Learning Approach. - Keyhan Najafian; Farhad Maleki; Lingling Jin; Ian Stavness (CoRR, 2025)