Match tier
Listed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-08-06
Y
Yihong Feng
Researcher
Faculty Researcher
Biological and Agricultural Engineering
10 h-index
42 pubs
368 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Yihong Feng's research focuses on the application of advanced computational techniques, particularly machine learning and artificial neural networks, to complex biological and medical problems. His work investigates the fundamental properties of learning dynamics in artificial neural networks, including their generalization capabilities, the impact of mislabeled data, and the relationship between learning dynamics and network architecture. Feng has explored the diagnostic value of deep learning in medical imaging, specifically for pancreatic tumors, and has also studied backdoor attacks in medical image analysis. His collaborations include work with researchers at the University of Arkansas at Fayetteville, resulting in multiple shared publications. Feng's scholarly contributions are reflected in his h-index of 10 and over 360 citations.
Metrics
- h-index: 10
- Publications: 42
- Citations: 368
Selected Publications
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Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification (2026)
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Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification (2026)
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Smartphone-enabled Depth-aware Transillumination Imaging for Detection of Chicken Breast Fillet Myopathies in Chicken Fillets (2026)
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Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation (2025)
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Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation (2025)
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Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression (2024)
Collaboration Network
Top Collaborators
Chaitanya Pallerla
University of Arkansas at Fayetteville
4 shared publications
In database
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
- Smartphone-enabled Depth-aware Transillumination Imaging for Detection of Chicken Breast Fillet Myopathies in Chicken Fillets
Pouya Sohrabipour
University of Arkansas at Fayetteville
3 shared publications
In database
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
Dongyi Wang
University of Arkansas at Fayetteville
3 shared publications
In database
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
Ramesh Bahadur Bist
University of Arkansas at Fayetteville
2 shared publications
In database
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Smartphone-enabled Depth-aware Transillumination Imaging for Detection of Chicken Breast Fillet Myopathies in Chicken Fillets
Amirreza Davar
University of Arkansas at Fayetteville
2 shared publications
In database
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
Casey Owens
University of Arkansas at Fayetteville
2 shared publications
In database
- Smartphone-enabled Depth-aware Transillumination Imaging for Detection of Chicken Breast Fillet Myopathies in Chicken Fillets
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
C.M. Owens
University of Arkansas at Fayetteville
1 shared publication
In database
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
Siavash Mahmoudi
University of Arkansas at Fayetteville
1 shared publication
In database
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
Xiaomin Lin
University of South Florida (US)
1 shared publication
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
Xiaomin Lin
University of South Florida (US)
1 shared publication
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
Arjun Suresh
University of Maryland, College Park (US)
1 shared publication
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
Philip G. Crandall
University of Arkansas at Fayetteville
1 shared publication
In database
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
Wan Shou
University of Arkansas at Fayetteville
1 shared publication
In database
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
Yu She
Purdue University West Lafayette (US)
1 shared publication
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
D Wang
University of Arkansas at Fayetteville
1 shared publication
In database
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
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