8 citations · 8 across the 6 of their papers we have counts for
6 papers
Selective Classifier-free Guidance for Zero-shot Text-to-speech
John Zheng, Farhad Maleki
In zero-shot text-to-speech, achieving a balance between fidelity to the target speaker and adherence to text content remains a challenge. While classifier-free guidance (CFG) stra…
FTIO: Frequent Temporally Integrated Objects
Mohammad Mohammadzadeh Kalati, Farhad Maleki, Ian McQuillan
Predicting and tracking objects in real-world scenarios is a critical challenge in Video Object Segmentation (VOS) tasks. Unsupervised VOS (UVOS) has the additional challenge of fi…
Rel-UNet: Reliable Tumor Segmentation via Uncertainty Quantification in nnU-Net
Seyed Sina Ziaee, Farhad Maleki, Katie Ovens
Accurate and reliable tumor segmentation is essential in medical imaging analysis for improving diagnosis, treatment planning, and monitoring. However, existing segmentation models…
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models
Farhad Maleki, Linda Moy, Reza Forghani +14
Deep learning techniques hold immense promise for advancing medical image analysis, particularly in tasks like image segmentation, where precise annotation of regions or volumes of…
Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls
Farhad Maleki, Katie Ovens, Rajiv Gupta +3
Purpose: Despite the potential of machine learning models, the lack of generalizability has hindered their widespread adoption in clinical practice. We investigate three methodolog…
Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? -- A Case Study using Dual Energy CT Data
Andreas Maier, Seung Hee Yang, Farhad Maleki +2
In the domain of medical image processing, medical device manufacturers protect their intellectual property in many cases by shipping only compiled software, i.e. binary code which…