Farhad Maleki

38 papers A 1B 1Misc 1Journal 19Unranked 16
YearRankTypeTitle / Venue / Authors
2025 — conf
A Semi-Self-Supervised Approach for Dense-Pattern Video Object Segmentation.
CVPR Workshops
Keyhan Najafian, Farhad Maleki, Lingling Jin, Ian Stavness
2025 — conf
Agri-FM+: A Self-Supervised Foundation Model for Agricultural Vision.
CVPR Workshops
Md Jaber Al Nahian, Tapotosh Ghosh, Farnaz Sheikhi, Farhad Maleki
2025 — conf
Decoder-Aware Self-Supervised Continual Pretraining and Uncertainty-Guided Pseudo-Labeling for Wheat Organ Segmentation.
ICCVW
Tapotosh Ghosh, Md Jaber Al Nahian, Farnaz Sheikhi, Farhad Maleki
2025 A conf
FTIO: Frequent Temporally Integrated Objects.
ECAI
Mohammad Mohammadzadeh Kalati, Farhad Maleki, Ian McQuillan
2025 J jnl
FTIO: Frequent Temporally Integrated Objects.
CoRR
Mohammad Mohammadzadeh Kalati, Farhad Maleki, Ian McQuillan
2025 J jnl
Federated Pseudo-Labeling: A Data-Centric, Privacy-Preserving Framework for Medical Image Segmentation.
IEEE J. Biomed. Health Informatics
Sidratul Montaha, Rashik Rahman, Tapotosh Ghosh, Farnaz Sheikhi, Farhad Maleki
2025 J jnl
From Semantic To Instance: A Semi-Self-Supervised Learning Approach.
CoRR
Keyhan Najafian, Farhad Maleki, Lingling Jin, Ian Stavness
2025 J jnl
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models.
J. Imaging Inform. Medicine
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, Atlas Haddadi Avval, Susan Sotardi, Neil A. Tenenholtz, Felipe Kitamura, Timothy Kline
2025 — conf
Rel-UNet: Reliable Tumor Segmentation via Uncertainty Quantification in nnU-Net.
ICCAI
S. Sina Ziaee, Farhad Maleki, Katie L. Ovens
2025 J jnl
Selective Classifier-free Guidance for Zero-shot Text-to-speech.
CoRR
John Zheng, Farhad Maleki
2025 J jnl
Should we pre-train a decoder in contrastive learning for dense prediction tasks?
CoRR
Sébastien Quetin, Tapotosh Ghosh, Farhad Maleki
2024 J jnl
Automatic segmentation of Organs at Risk in Head and Neck cancer patients from CT and MRI scans.
CoRR
Sébastien Quetin, Andrew Heschl, Mauricio Murillo, Rohit Murali, Shirin A. Enger, Farhad Maleki
2024 — conf
Beyond Annotations: Efficient Wheat Head Segmentation Using L-Systems, Game Engines, and Student-Teacher Models.
ECCV Workshops (3)
Hosein Beheshtifard, Elijah Mickelson, Keyhan Najafian, Farhad Maleki
2024 J jnl
DVOS: Self-Supervised Dense-Pattern Video Object Segmentation.
CoRR
Keyhan Najafian, Farhad Maleki, Ian Stavness, Lingling Jin
2024 — conf
Discovering Knowledge Embedded in Gene Set Databases: A Mathematical Modelling Approach.
ICCBB
Katie L. Ovens, Ebunoluwa Makinde, Samuel Horovatin, Elham Rezaei, Alan M. Rosenberg, Lingling Jin, Ian McQuillan, Anthony J. Kusalik, Farhad Maleki
2024 J jnl
Efficient Wheat Head Segmentation with Minimal Annotation: A Generative Approach.
J. Imaging
Jaden Myers, Keyhan Najafian, Farhad Maleki, Katie L. Ovens
2024 J jnl
Modified CycleGAN for the synthesization of samples for wheat head segmentation.
CoRR
Jaden Myers, Keyhan Najafian, Farhad Maleki, Katie L. Ovens
2024 J jnl
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models.
CoRR
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, Atlas Haddadi Avval, Susan Sotardi, Neil A. Tenenholtz, Felipe Kitamura, Timothy Kline
2024 J jnl
Semi-Self-Supervised Domain Adaptation: Developing Deep Learning Models with Limited Annotated Data for Wheat Head Segmentation.
Algorithms
Alireza Ghanbari, Gholam Hassan Shirdel, Farhad Maleki
2024 J jnl
Semi-Self-Supervised Domain Adaptation: Developing Deep Learning Models with Limited Annotated Data for Wheat Head Segmentation.
CoRR
Alireza Ghanbari, Gholam Hassan Shirdel, Farhad Maleki
2024 — conf
SynthSet: Generative Diffusion Model for Semantic Segmentation in Precision Agriculture.
ECCV Workshops (3)
Andrew Heschl, Mauricio Murillo, Keyhan Najafian, Farhad Maleki
2024 J jnl
SynthSet: Generative Diffusion Model for Semantic Segmentation in Precision Agriculture.
CoRR
Andrew Heschl, Mauricio Murillo, Keyhan Najafian, Farhad Maleki
2023 — conf
Deep Learning-Based Hierarchical Delineation of Kidneys, Tumors, and Cysts in CT Images.
KiTS@MICCAI
Andrew Heschl, Hosein Beheshtifard, Phuong Thao Nguyen, Tapotosh Ghosh, Katie L. Ovens, Farhad Maleki
2022 J jnl
Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls.
CoRR
Farhad Maleki, Katie L. Ovens, Rajiv Gupta, Caroline Reinhold, Alan Spatz, Reza Forghani
2022 — conf
Offer Proprietary Algorithms Still Protection of Intellectual Property in the Age of Machine Learning? - A Case Study Using Dual Energy CT Data.
Bildverarbeitung für die Medizin
Andreas K. Maier, Seung Hee Yang, Farhad Maleki, Nikesh Muthukrishnan, Reza Forghani
2021 — conf
A Deep Learning-Based Pipeline for Celiac Disease Diagnosis Using Histopathological Images.
CAIP (1)
Farhad Maleki, Kevin Cote, Keyhan Najafian, Katie L. Ovens, Yan Miao, Rita Zakarian, Caroline Reinhold, Reza Forghani, Peter Savadjiev, Zu-hua Gao
2021 — conf
A Semi-self-supervised Learning Approach for Wheat Head Detection using Extremely Small Number of Labeled Samples.
ICCVW
Keyhan Najafian, Alireza Ghanbari, Ian Stavness, Lingling Jin, Gholam Hassan Shirdel, Farhad Maleki
2021 J jnl
Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? - A Case Study using Dual Energy CT Data.
CoRR
Andreas K. Maier, Seung Hee Yang, Farhad Maleki, Nikesh Muthukrishnan, Reza Forghani
2021 J jnl
Juxtapose: a gene-embedding approach for comparing co-expression networks.
BMC Bioinform.
Katie L. Ovens, Farhad Maleki, B. Frank Eames, Ian McQuillan
2019 — conf
Crop Lodging Prediction From UAV-Acquired Images of Wheat and Canola Using a DCNN Augmented With Handcrafted Texture Features.
CVPR Workshops
Sara Mardanisamani, Farhad Maleki, Sara Hosseinzadeh Kassani, Sajith Rajapaksa, Hema Sudhakar Duddu, Menglu Wang, Steve Shirtliffe, Seungbum Ryu, Anique Josuttes, Ti Zhang, Sally Vail, Curtis Pozniak, Isobel Parkin, Ian Stavness, Mark G. Eramian
2019 J jnl
Crop Lodging Prediction from UAV-Acquired Images of Wheat and Canola using a DCNN Augmented with Handcrafted Texture Features.
CoRR
Sara Mardanisamani, Farhad Maleki, Sara Hosseinzadeh Kassani, Sajith Rajapaksa, Hema Sudhakar Duddu, Menglu Wang, Steve Shirtliffe, Seungbum Ryu, Anique Josuttes, Ti Zhang, Sally Vail, Curtis Pozniak, Isobel Parkin, Ian Stavness, Mark G. Eramian
2019 — conf
Gene Set Databases: A Fountain of Knowledge or a Siren Call?
BCB
Farhad Maleki, Katie L. Ovens, Ian McQuillan, Elham Rezaei, Alan M. Rosenberg, Anthony J. Kusalik
2019 — conf
Gene Set Overlap: An Impediment to Achieving High Specificity in Over-representation Analysis.
BIOINFORMATICS
Farhad Maleki, Anthony J. Kusalik
2019 J jnl
Measuring consistency among gene set analysis methods: A systematic study.
J. Bioinform. Comput. Biol.
Farhad Maleki, Katie L. Ovens, Daniel J. Hogan, Elham Rezaei, Alan M. Rosenberg, Anthony J. Kusalik
2019 — conf
Method Choice in Gene Set Analysis Has Important Consequences for Analysis Outcome.
BIOINFORMATICS
Farhad Maleki, Katie L. Ovens, Elham Rezaei, Alan M. Rosenberg, Anthony J. Kusalik
2018 — conf
Sample Size and Reproducibility of Gene Set Analysis.
BIBM
Farhad Maleki, Katie L. Ovens, Ian McQuillan, Anthony J. Kusalik
2010 Misc conf
A CA Randomizers Based on parallel CAs with Balanced Rules.
ICCS
Farhad Maleki, Ali Mohades, Mohammad E. Shiri, Afsane Bijari
2008 B conf
An Image Encryption System by Cellular Automata with Memory.
ARES
Farhad Maleki, Ali Mohades, S. Mehdi Hashemi, Mohammad E. Shiri