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About the database ScholarIQanswers from OpenAlex & ORCID
How has Haseeb Nazki's publication output changed over time?
ScholarIQpublication output · 2019–2024
Output declined33% over the shown period — from 3 works in 2019 to 2 in 2024.
3
1
1
1
2
20192020202220232024
What are the most-cited papers on Haseeb Nazki?
ScholarIQmost cited works
Artificial Intelligence Approach for Tomato Detection and Mass Estimation in Precision Agriculture
Jae-Su Lee, Haseeb Nazki, Jeonghyun Baek, Youngsin Hong, Meonghun Lee
Sustainability. 202084 CitationsOPEN ACCESS
Image-to-Image Translation with GAN for Synthetic Data Augmentation in Plant Disease Datasets
Haseeb Nazki, John J. Lee, Sook Yoon, Dong Sun Park
Korean Institute of Smart Media. 201945 Citations
MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception Loss
Haseeb Nazki, Ognjen Arandjelović, In Hwa Um, David J. Harrison
202315 CitationsOPEN ACCESS
Unsupervised image translation using adversarial networks for improved plant disease recognition
Haseeb Nazki, Sook Yoon, Alvaro Fuentes, Dong Sun Park
Computers and Electronics in Agriculture. 20199 CitationsOPEN ACCESS
MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception Loss
Haseeb Nazki, Ognjen Arandjelović, Inhwa Um, David J. Harrison
arXiv (Cornell University). 20222 CitationsOPEN ACCESS
Related on ScholarIQ
University of St Andrews
Institution
Artificial Intelligence Approach for Tomato Detection and Mass Estimation in Precision Agriculture
Paper
Image-to-Image Translation with GAN for Synthetic Data Augmentation in Plant Disease Datasets
Paper
MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception Loss
Paper
Unsupervised image translation using adversarial networks for improved plant disease recognition
Paper
MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception Loss
Paper