Match tier
Listed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-06
Y
Yihong Feng
Role not yet determined Is this you? Add your title
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 investigates the application of machine learning and computational methods to biological and medical problems. His work includes developing models for neurological processes and analyzing medical data. Feng has published research on topics such as backdoor attacks in medical image analysis, the relationship between inverse variance and flatness in stochastic gradient descent for finding optimal model parameters, and the activity-weight duality in feed-forward neural networks to improve generalization. He also has a publication on assessing the unidimensionality of polytomous data and another on the diagnostic value of deep learning in endoscopic ultrasound for pancreatic tumors.
His scholarship metrics include an h-index of 10, with 42 total publications and 368 citations. Feng collaborates with several faculty members at the University of Arkansas at Fayetteville, including Chaitanya Pallerla, Pouya Sohrabipour, C.M. Owens, and Amirreza Davar.
Metrics
- h-index: 10
- Publications: 42
- Citations: 368
Positions
-
Research Intern 2020IBM Thomas J Watson Research Center ORCID
Selected Publications
-
Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification (2026)
-
Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification (2026)
-
Smartphone-enabled Depth-aware Transillumination Imaging for Detection of Chicken Breast Fillet Myopathies in Chicken Fillets (2026)
-
Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation (2025)
-
Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation (2025)
-
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 Kumar Reddy 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
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
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
- Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification
Dongyi Wang
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
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
- Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification
Amirreza Davar
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
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
- Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification
Philip G. Crandall
University of Arkansas at Fayetteville
3 shared publications
In database
- Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
- Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification
Casey M. Owens
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
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
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
Jeyamkondan Subbiah
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
Avisekh Tripathy
University of Arkansas at Fayetteville
2 shared publications
In database
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
- Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification
Yang Tian
University of Arkansas at Fayetteville
2 shared publications
In database
- Assessing the Feasibility of Low-Cost Multispectral Sensing for Woody Breast Severity Classification
- Assessing the feasibility of low-cost multispectral sensing for woody breast severity classification
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
Similar Researchers
Based on overlapping research topics
Reeshad Khan
University of Arkansas at Fayetteville
Advanced Neural Network Applications
Machine Learning Applications
Medical Imaging Techniques and Applications
Muhammed Mohaimin Sadiq
University of Arkansas at Little Rock
Advanced Neural Network Applications
Machine Learning Applications
Medical Imaging Techniques and Applications
Pooja Modi
University of Arkansas for Medical Sciences
Machine Learning Applications
Medical Imaging Techniques and Applications
Neurological disorders and treatments
Shaharina Shoha
Arkansas State University
Advanced Neural Network Applications
Machine Learning Applications
Medical Imaging Techniques and Applications
Thanh-Dat Truong
Arkansas State University
Advanced Neural Network Applications
Machine Learning Applications
Medical Imaging Techniques and Applications
Tran-Dac-Thinh Phan
University of Arkansas at Fayetteville
Advanced Neural Network Applications
Machine Learning Applications
Medical Imaging Techniques and Applications