Publications

Google Scholar

Book Chapters

  1. H. Hao, E.R. Bartusiak, D. Güera, D. Mas Montserrat, S. Baireddy, Z. Xiang, S. Yarlagadda, R. Shao, J, Horvath, J. Yang, F. Zhu, E.J. Delp, “Chapter 11: Deepfake Detection Using Multiple Data Modalities,” Handbook of Digital Face Manipulation and Detection, Springer, Advances in Computer Vision and Pattern Recognition, C. Rathged et al (eds.), Chapter 11, Nov 2021.

  2. L. Liu, F. Zhu, M. Bosch, and E. J. Delp, “Recent Advances in Video Compression,” in Statistical Science and Interdisciplinary Research, Vol. 2, Advances in Intelligent Information Processing, B Chanda Ed. India: World Scientific, 2008, pp. 191-208.

Journal Articles

  1. Z. Duan, M. Lu, J. Ma, Y. Huang, Z. Ma, F. Zhu, “QARV: Quantization-Aware ResNet VAE for Lossy Image Compression,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 1, p. 436 – 450, Oct 2023. Code

  2. L. Lin, J. He, F. Zhu, E. J. Delp, H. A. Eicher-Miller, “Integration of USDA Food Classification System and Food Composition Database for Image-Based Dietary Assessment among Individuals Using Insulin,” Nutrients, vol. 15, no. 14, p. 3183, Jul 2023.

  3. J. He, L. Lin, H. Eicher-Miller, F. Zhu, “Long-Tailed Food Classification,” Nutrients, vol. 15, no. 12, p. 2751, Jun 2023.

  4. Y. Dong, G.S. Fraley, J.M. Siegford, F. Zhu, M.A. Erasmus, “Comparing different environmental enrichments for improving the welfare and walking ability of male turkeys,” PLOS ONE, Apr 2023.

  5. Z. Duan, Z. Ma, F. Zhu, “Unified Architecture Adaptation for Compressed Domain Semantic Inference,” IEEE Transactions on Circuits and Systems for Video Technology, Jan 2023.

  6. L. Lin, F. Zhu, E.J. Delp, H.A. Eicher-Miller, “Differences in Dietary Intake Exist Among U.S. Adults by Diabetic Status Using NHANES 2009-2016,” Nutrients, vol. 14, no. 16, p. 3284, Aug 2022.

  7. M.K. Fialkowski, J. Kai, C. Young, G. Langfelder, J. Ng-Osorio, Z. Shao, F. Zhu, D.A. Kerr, C.J. Boushey, “An Active Image-Based Mobile Food Record is Feasible for Capturing Eating Occasions Among Infants Ages 3 - 12 Months Old in Hawaiʻi,” Nutrients, Vol. 14, no. 5, p. 1075, Mar 2022.

  8. K. Yonemori, L. Zuccarelli, L.L Mechant, F. Zhu, D. Kerr, C.J. Boushey, “Temporal patterns of eating by mode of data collection from the baseline dietary intakes of participants in the Healthy Diet and Lifestyle Study,” Journal of Food Composition and Analysis, vol. 107, p. 104296, Dec 2021.

  9. C. Whitton, J. D. Healy, C. E. Collins, B. Mullan, M. E. Rollo, S. S. Dhaliwal, R. Norman, C. J. Boushey, E. J. Delp, F. Zhu, T. A. McCaffrey, S. I. Kirkpatrick, P. Atyeo, S. A. Mukhtar, J. L. Wright, C. Ramos-García, C. M. Pollard, and D. A. Kerr, “Accuracy and Cost-effectiveness of Technology-Assisted Dietary Assessment Comparing the Automated Self-administered Dietary Assessment Tool, Intake24, and an Image-Assisted Mobile Food Record 24-Hour Recall Relative to Observed Intake: Protocol for a Rand,” JMIR Research Protocols, vol. 10, no. 12, p. e32891, Dec 2021.

  10. K. Danible, C. Panizza, C.J. Boushey, D.A. Kerr, F. Zhu, J.C. Banna, “A Novel Tool for Measuring Food Waste: The Mobile Food Record,” Journal of Extension, vol. 59, no. 3, Jul 2021.

  11. S. Yarlagadda, D. Mas Montserrat, D. Güera, C. Boushey, D. Kerr, F. Zhu, “Saliency-Aware Class-Agnostic Food Image Segmentation,” ACM Transaction on Healthcare and Computing, vol. 2, no. 3, pp. 1-17, Jul 2021.

  12. D. Ding, M. Zhan, D. Chen, Q. Chen, Z. Liu, F. Zhu, “Advances In video Compression System Using Deep Neural Network: A Review and Case Studies,” Proceedings of the IEEE, pp. 1-27, Mar 2021. Project Page

  13. Y. Qin, M. Aqeel, F. Zhu, E.J. Delp, H.A. Eicher-Miller, “Dietary Aspects to Incorporate in the Creation of a Mobile Image-Based Dietary Assessment Tool to Manage and Improve Diabetes,” Nutrients, vol. 13, no. 4, pp. 1179, Apr 2021.

  14. D. Ding, L. Kong, L. Chen, F. Zhu, “A Progressive CNN In-loop Filtering Approach for Inter Frame Coding,” Signal Processing: Image Communication, vol. 94, pp. 116201, Feb 2021. Code

  15. H. O’Reilly, C. Panizza, U. Lim, K. M. Yonemori, L. R. Wilkens, Y. B. Shvetsov, M. N. Harvie, J. Shepherd, F. Zhu, L. L. Marchand, C. J Boushey, K. D. Cassel, “Utility of self-rated adherence for monitoring dietary and physical activity compliance and assessment of participant feedback of the Healthy Diet and Lifestyle Study pilot,” Pilot and Feasibility Studies, vol. 7, no. 1, pp. 48, Feb 2021.

  16. S. Campbell, J. Chen, C.J. Boushey, H. Eicher-Miller, F. Zhu, M.K. Fialkowski, “Food Security and Diet Quality in Native Hawaiian, Pacific Islander, and Filipino Infants 3 to 12 Months of Age,” Nutrients, vol. 12, no. 7, Jul 2020.

  17. M.K. Fialkowski, J. Ng-Osorio, J. Kai, K. Swafford, G. Langfelder, C.G. Young, J.J. Chen, F. Zhu, C.J. Boushey, “Type, Timing and Diversity of Complementary Foods Among Native Hawaiian, Pacific Islander and Filipino Infants,” Hawai’i Journal of Health & Social Welfare, vol. 79, no. 5, pp. 127-134, May 2020.

  18. N. Alshurafa, AW. Lin, F. Zhu, R. Ghaffari, J. Hester, E.J. Delp, J. Rogers, B. Spring, “Counting Bites with Bits: Expert Workshop Addressing Monitoring Calorie and Macronutrient Intake,” Journal of Medical Internet Research, vol. 21, no. 12, Dec 2019.

  19. S. Fang, Z. Shao, D.A. Kerr, C.J. Boushey, F. Zhu, “[https:pubmed.ncbi.nlm.nih.gov31003547 An End-to-End Image-Based Automatic Food Energy Estimation Technique Based on Learned Energy Distribution

  20. R. Halse, C. Shoneye, C.M. Pollard, J. Jancey, J.A. Scott, I. Pratt, S. Dhaliwal, R. Norman, L. Straker, C.J. Boushey, E.J. Delp, F. Zhu, A. Haray, M. Syzbiak, A. Finch, J. McVeigh, B. Mullan, C.E. Collins, A. Mukhtar, K. Edwards, J. Healy, D. A. Kerr, “Improving Nutrition and Activity Behaviors Using Digital Technology and Tailored Feedback: Protocol for the Tailored Diet and Activity (ToDAy) Randomized Controlled Trial,” Journal of Medical Internet Research Protocols, vol. 8, no. 2, pp. e12782, Feb 2019.

  21. C.L. Shoneye, S.S. Dhaliwal, C.M. Pollard, C.J. Boushey, E.J. Delp, A.J. Harray, P.A. Howat, M. Hutchesson, M.E. Rollor, F. Zhu, J.L. Wright, I.S. Pratt, J. Jancey, R. Halse, J.A. Scott, B. Mullan, C.E. Collins, D.A. Kerr, “Image-based dietary assessment and tailored feedback using mobile technology: mediating behavior change in young adults,” Nutrients, vol. 11, no. 2, pp. 435, Feb 2019.

  22. M. Polfuss, A. Moosreiner, C. J. Boushey, E. J. Delp, F. Zhu, “Technology-Based Dietary Assessment in Youth With and Without Developmental Disabilities,” Nutrients, vol. 10, no. 10, pp. 1482, Oct 2018.

  23. Y. Wang, Y. He, C.J. Boushey, F. Zhu, E.J. Delp, “Context based Image Analysis with Application in Dietary Assessment and Evaluation,” Multimedia Tools and Applications, Nov 2017, pp. 1-26.

  24. C.J. Boushey, M. Spoden, E.J. Delp, F. Zhu, M. Bosch, Z. Ahmad, Y.B. Shvetsov, J.P. DeLany, D.A. Kerr, “Report Energy Intake Accuracy Compared to Doubly Labeled Water and Usability of the Mobile Food Record among Community Dwelling Adult,” Nutrients, vol. 9, no. 3, pp. 312, Mar 2017.

  25. D.A. Kerr, S.S. Dhaliwal, C.M. Pollard, R. Norman, J.L. wright, A.J. Harray, C.L. Shoneye, V.A. Solah, W.J. Hunt, F. Zhu, E.J. Delp, C.J. Boushey, “BMI is Associated with the Willingness to Record Diet with a Mobile Food Record among Adults Participating in Dietary Interventions,” Nutrients, vol. 9, no. 3, pp. 244, Mar 2017.

  26. C.J. Boushey, M. Spoden, F. Zhu, E.J. Delp, D.A. Kerr, “New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods,” Proceedings of the Nutrition Society, vol. 76, no. 3, pp. 283-294, Aug 2017.

  27. F. Zhu, M. Bosch, N. Khanna, C. J. Boushey, and E. J. Delp, “Multiple Hypotheses Image Segmentation and Classification with Application to Dietary Assessment,” IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 1, pp. 377-388, Jan 2015.

  28. T.E. Schap, F. Zhu, E.J. Delp, and C.J. Boushey, “Merging Dietary Assessment with the Adolescent Lifestyle,” Journal of Human Nutrition and Dietetics, vol. 27, pp. 82-88, Jan 2014.

  29. B.L. Daugherty, T.E. Schap, R. Ettienne-Gittens, F. Zhu, M. Bosch, E.J. Delp, D.S. Ebert, D.A. Kerr, C.J. Boushey, “Novel Technologies for Assessing Dietary Intake: Evaluating the Usability of a Mobile Telephone Food Record among Adults and Adolescents,” Journal of Medical Internet Research, vol. 14, no. 2, pp. e58, Apr 2012.

  30. M. Bosch, F. Zhu and E.J. Delp, “Segmentation Based Video Compression Using Texture and Motion Models,” IEEE Journal of Selected Topics in Signal Processing, vol. 5, no. 7, pp. 1366-1377, Nov 2011.

  31. F. Zhu, M. Bosch, I. Woo, S. Kim, C. J. Boushey, D. S. Ebert, and E. J. Delp, “The Use of Mobile Devices in Aiding Dietary Assessment and Evaluation,” IEEE Journal of Selected Topics in Signal Processing, vol. 4, no. 4, pp. 756 - 766, Aug 2010.

  32. B.L. Six, T.E. Schap, F. Zhu, A. Mariappan, M. Bosch, E.J. Delp, D.S. Ebert, D.A. Kerr, and C.J. Boushey, “Evidence-Based Development of a Mobile Telephone Food Record,” Journal of American Dietetic Association, vol. 110, no. 1, pp. 74-79, Jan 2010.

Selected Conference Proceedings

  1. Z. Duan, M. Lu, J. YangG, J. He, Z. Ma, F. Zhu, “Towards Backward-Compatible Continual Learning of Image Compression,” Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, Jun 2024.

  2. J. He, F. Zhu, “Gradient Reweighting: Towards Imbalanced Class-Incremental Learning,” Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, Jun 2024.

  3. Y. Zhang, Z. Duan, M. Lu, D. Ding, F. Zhu, Z. Ma, “Another Way to the Top: Exploit Contextual Clustering in Learned Image Coding,” Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 2024.

  4. M. Lu, Z. Duan, F. Zhu, Z. Ma, “Deep Hierarchical Video Compression,” Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 2024.

  5. S. Raghavan, J. He, F. Zhu, “Online Class-Incremental Learning For Real-World Food Image Classification,” Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA, Jan 2024. Code

  6. X. Pan, J. He, F. Zhu, “Muti-Stage Hierarchical Food Classification,” Proceedings of the ACM International Conference on Multimedia Workshop (ACMMM-W, MADiMA), Ottawa, Canada Oct 2023.

  7. Y. Han, J. He, M. Gupta, EJ. Delp, F. Zhu, “Diffusion Model with Clustering-based Conditioning for Food Image Generation,” Proceedings of the ACM International Conference on Multimedia Workshop (ACMMM-W, MADiMA), Ottawa, Canada Oct 2023.

  8. J. Ma, J. He, F. Zhu, “An Improved Encoder-Decoder Framework for Food Energy Estimation,” Proceedings of the ACM International Conference on Multimedia Workshop (ACMMM-W, MADiMA), Ottawa, Canada Oct 2023.

  9. W. Xu, Y. Shen, Q. Lin, J. Allebach, F. Zhu, “Exploiting Temporal Information in Real-Time Portrait Video Segmentation,” Proceedings of the ACM International Conference on Multimedia Workshop (ACMMM-W, HCMA), Ottawa, Canada, Oct 2023.

  10. [Student Paper Contest Finalist] X. Pan, J. He, F. Zhu, “Personalized Food Image Classification: Benchmark Datasets and New Baseline,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove (Asilomar), CA, USA, Oct 2023.

  11. Y. Huang, T. Wang, Q. Lin, J. Allebach, F. Zhu, “Efficient Joint Video Denoising and Super-Resolution,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Kuala Lumpur, Malaysia, Oct 2023.

  12. J. He, F. Zhu, “Single-Stage Heavy-Tailed Food Classification,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Kuala Lumpur, Malaysia, Oct 2023.

  13. Z. Duan, J. Ma, J. HePD, F. Zhu, “An Improved Upper Bound on the Rate-Distortion Function of Images,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Kuala Lumpur, Malaysia, Oct 2023. code

  14. M Hossain, Z. Duan, Y. Huang, F. Zhu, “Flexible Variable-Rate Image Feature Compression for Edge-Cloud Systems,” Proceedings of the IEEE International Conference on Multimedia and Expo Workshop (ICME-W), Brisbane, Australia, Jul 2023.

  15. Y. Huang, Z. Duan, F. Zhu, “NARV: An Efficient Noise-Adaptive ResNet VAE for Joint Image Compression and Denoising,” Proceedings of the IEEE International Conference on Multimedia and Expo Workshop (ICME-W), Brisbane, Australia, Jul 2023.

  16. Y. Shen, W. Xu, Q. Lin, J.P. Allebach, F. Zhu, “Real-Time End-to-End Portrait and In-Hand Object Segmentation with Background Fusion,” Proceedings of the IEEE International Conference on Multimedia and Expo Workshop (ICME-W), Brisbane, Australia, Jul 2023.

  17. J. Yang, X. Ji, J. Wei, Y. Huang, S. Zhang, Q. Lin, J. Allebach, F. Zhu, “VR Facial Expression Tracking Using Locally Linear Embedding,” Proceedings of the IEEE International Conference on Multimedia and Expo Workshop (ICME-W), Brisbane, Australia, Jul 2023.

  18. X. Ji, J. Yang, J. Wei, Y. Huang, S. Zhang, Q. Lin, J. Allebach, F. Zhu, “Classifier Guided domain Adaptation for VR Facial Expression Tracking,” Proceedings of the IEEE International Conference on Multimedia and Expo Workshop (ICME-W), Brisbane, Australia, Jul 2023.

  19. Z. Shao, G. Vinod, J. He, F. Zhu, “An End-to-End Food Portion Estimation Framework Based on Shape Reconstruction from Monocular Image,” Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), Brisbane, Australia, Jul 2023.

  20. [Best Algorithms Paper] Z. Duan, M. Lu, Z. Ma, and F. Zhu, “Lossy Image Compression with Quantized Hierarchical VAEs,” Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA, Jan 2023. Code

  21. [Best Paper Award Finalists] Z. Duan, F. Zhu, “Efficient Feature Compression for Edge-Cloud Systems,” Proceedings of the Picture Coding Symposium (PCS), San Jose, California, USA, Dec 2022. Code

  22. Z. Duan, M. Lu, Z. Ma, F. Zhu, “Opening the Black Box of Learned Image Coders,” Proceedings of the Picture Coding Symposium (PCS), San Jose, California, USA, Dec 2022.

  23. X. Pan, J, He, A. Peng, F. Zhu, “Simulating Personal food consumption Patterns Using a Modified Markov Chain,” Proceedings of the ACM Multimedia Workshop (MADiMa)(ACMMM-W), Lisbon, Portugal, Oct 2022.

  24. J. He, F. Zhu, “Exemplar-Free Online Continual Learning,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Anchorage, Bordeaux, France, Oct 2022.

  25. G. Vinod, Z. Shao, F. Zhu, “Image Based Food Portion Estimation With Depth Domain Adaptation,” Proceedings of the IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), Aug 2022.

  26. J. He, F. Zhu, “Out-Of-Distribution Detection In Unsupervised Continual Learning,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPR-W), Jun 2022.

  27. J. He, F. Zhu, “Online Continual Learning Via Candidates Voting,” Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), Jan 2022.

  28. Z. Shao, Y. Han, J. He, R. Mao, J. Wright, D. Kerr, C. Boushey, F. Zhu, “An Integrated System for Mobile Image-Based Dietary Assessment,” Proceedings of the ACM Multimedia Workshop (AIxFood) (ACMMM-W), Oct 2021.

  29. J. He, F. Zhu, “Online Continual Learning for Visual Food Classification,” Proceedings of the IEEE International Conference on Computer Vision Workshop (ICCV-W), virtual, Oct 2021.

  30. R. Mao, J. He, L. Lin, Z. Shao, H. Eicher-Miller, F. Zhu, “Improving Dietary Assessment Via Integrated Hierarchy Food Classification,” Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP), Tampere, Finland, Oct 2021.

  31. Z. Shao, F. Shao, R. Mao, J. He, J. Wright, D. Kerr, C. Boushey, F. Zhu, “Towards Learning Food Portion From Monocular Images With Cross-Domain Feature Adaptation,” Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP), Tampere, Finland, Oct 2021.

  32. J. He, F. Zhu, “Unsupervised Continual Learning Via Pseudo Labels,” Proceedings of the International Joint Conference on Artificial Intelligence Workshop (IJCAI-W), virtual, Aug 2021.

  33. R. Mao, M. Tweardy, S. Wegerich, C. Goergen, G.R. Wodicka, F. Zhu, “Motion Artifact Reduction In Photoplethysmography For Reliable Signal Selection,” Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), virtual, Oct 2021.

  34. S. Ju, M.A. Erasmus, F. Zhu, A.R. Reibman, “Turkey Behavior Identification using Video Analytics and Object Tracking,” Proceedings of the IEEE International Conference on Image Processing (ICIP), virtual, Sep 2021.

  35. R. Mao, J. He, Z. Shao, S. Yarlagadda, F. Zhu, “Visual Aware Hierarchy Based Food Recognition,” Proceedings of the International Conference on Pattern Recognition (ICPR) Workshop, virtual, Jan 2021.

  36. J. He, Z. Shao, J. Wright, D. A. Kerr, C. J. Boushey, F. Zhu, “Multi-Task Image-Based Dietary Assessment for Food Recognition and Portion Size Estimation,” Proceedings of IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR), Shenzhen, China, Aug 2020. (invited paper)

  37. D. Montserrat, H. Hao, S. Yarlagadda, S. Baireddy, R. Shao, J. Horváth, E. Bartusiak, J. Yang, D. Güera, F. Zhu, E.J. Delp, “Deepfakes Detection with Automatic Face Weighting,” Proceedings of CVPR workshop on Media Forensics, Seattle, WA, USA, Jun 2020.

  38. J. He, R. Mao, Z, Shao, F. Zhu, “Incremental Learning In Online Scenario,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, Jun 2020.

  39. S. Yarlagadda, S. Baireddy, D. Güera, C. J. Boushey, D. A. Kerr, F. Zhu, “Learning Eating Environments Through Scene Clustering,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.

  40. P. Singh, S.M. Lindshield, F. Zhu, A. R. Reibman, “Animal Localization in Camera-Trap Images with Complex Background,” Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), Santa Fe, NM, USA, Mar 2020.

  41. S. Ju, M. A. Erasmus, A. R. Reibman, F. Zhu, “Video Tracking to Monitor Turkey Welfare,” Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), Santa Fe, NM, USA, Mar 2020.

  42. Z. Shao, R. Mao, F. Zhu, “Semi-Automatic Crowdsourcing Tool for Online Food Image Collection and Annotation,” IEEE BigData Workshop on Big Food and Nutrition Data Management and Analysis (Big Data), Los Angeles, USA, Dec 2019.

  43. J. Horváth, D. Buera, S. Yarlagadda, P. Bestagini, F. Zhu, S. Tubaro, E.J. Delp, “Anomaly-Based Manipulation Detection in Satellite Images,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshop ( (CVPR-W), Long Beach, CA, USA, Jun 2019.

  44. S. Yarlagadda, D. Güera, D. Montserrat, F. Zhu, P. Bestagini, S. Tubaro, E.J. Delp, “Shadow Removal Detection and Localization for Forensics Analysis,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019.

  45. D. Chen, Q. Chen, F. Zhu, “Pixel-Level Texture Segmentation Based AV1 Video Compression,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019.

  46. Q. Chen, R. Abu-Zhaya, A. Seidl, F. Zhu, “CNN Based Touch Interaction Detection For Infant Speech Development,” Proceedings of IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR), San Jose, California, USA, Mar 2019. (invited paper)

  47. E.R. Bartusiak, S. Yarlagadda, D. Güera, P. Bestagini, S. Tubaro, F. Zhu, E.J. Delp, “Splicing Detection And Localization In Satellite Imagery Using Conditional GANs,” Proceedings of IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR), San Jose, California, USA, Mar 2019. (invited paper)

  48. [Best Student Paper] J. He, K. Ziga, J. Bagchi, F. Zhu, “CNN Based Parameter Optimization for Texture Synthesis,” Electronic Imaging, Burlingame, CA, USA, Jan 2019.

  49. Z. Gu, S. Wang, F. Zhu, “Endmember Dictionary Based Hyperspectral Image Unmixing,” Proceedings of IEEE Global Conference on Signal and Information (GlobalSIP), Anaheim, California, USA, Nov 2018.

  50. S. Fang, Z. Shao, R. Mao, C. Fu, D. A. Kerr, C. J. Boushey, E. J. Delp, F. Zhu, “Single-View Food Portion Estimation: Learning Image-to-Energy Mapping Using Generative Adversarial Networks,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Athens, Greece, Oct 2018.

  51. Q. Chen, F. Zhu, “https:doi.org10.1109ICMEW.2018.8551542 Long Term Hand Tracking with Proposal Selection],” Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), San Diego, CA, USA, Jul 2018.

  52. S. Fang, C. Liu, K. Tahboub, F. Zhu, C. J. Boushey, E. J. Delp, “cTADA: The Design of a Crowdsourcing Tool for Online Food Image Identification and Segmentation,” IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), Las Vegas, NV, USA, Apr 2018.

  53. S. Yarlagadda, F. Zhu, “A Reflectance Based Method for Shadow Detection and Removal,” IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), Las Vegas, NV, USA, Apr 2018.

  54. D. Güera, F. Zhu, S.K. Yarlagadda, S. Tubaro, P. Bestagini and E.J. Delp, “Reliability Map Estimation for CNN-Based Camera Model Attribution,” Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, NV, USA, Mar 2018, pp. 964-973.

  55. S. Fang, F. Zhu, C. J. Boushy, E. J. Delp, “The Use of Co-Occurrence Patterns in Single Image Based Food Portion Estimation,” Proceedgins of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), Montreal, Canada, Nov 2017.

  56. Y. Wang, F. Zhu, C. J. Boushey, E. J. Delp, “Weakly Supervised Food Image Segmentation Using Class Activation Maps,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Beijing, China, Sep 2017.

  57. Y. Wang, J. Ribera, C. Liu, S, Yarlagadda, F. Zhu, “Pill Recognition Using Minimal Labelled Data,” Proceedings of the IEEE International Conference on Multimedia Big Data (BigMM), Laguna Hills, CA, USA, April 2017.

  58. Y. Wang, S, Fang, C. Liu, F. Zhu, D. A. Kerr, C. J. Boushey, E. J. Delp, “Food Image Analysis: The Big Data Problem You Can Eat!” Proceedings of the Annual Asilomar Conference on Signals, Systems, and Computers (Asilomar), Pacific Grove, CA, USA, Nov 2016.

  59. Z. Ahmad, M. Bosch, N. Khanna, D. A. Kerr, C. J. Boushey, F. Zhu, E. J. Delp. “A Mobile Food Record for Integrated Dietary Assessment,” Proceedings of the ACM International Conference on Multimedia Workshop (ACMMM-W, MADiMA), Amsterdam, The Netherlands, pp. 53-62, Oct 2016. DOI: 10.1145/2986035.2986038

  60. Y. Wang, C. Liu, F. Zhu, C. J. Boushey, E. J. Delp, “Efficient Superpixel based Segmentation for Food Image Analysis,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Phoenix, AZ, USA, Sep 2016.

  61. S. Fang, F. Zhu, C. Jiang, S. Zhang, C. J. Boushey, E. J. Delp, “A Comparison of Food Portion Size Estimation Using Geometric Models and Depth Images,” Proceedings of the IEEE International Conference on Image Processing (ICIP), Phoenix, AZ, USA, Sep 2016.

  62. S. Fang, C. Liu, F. Zhu, C. J. Boushey, E.J. Delp, “Single-View Food Portion Estimation Based on Geometric Models,” Proceedings of IEEE International Symposium on Multimedia (ISM), pp. 385-390, Miami, USA, Dec 2015.

  63. S. Fang, C. Liu, F. Zhu, C. J. Boushey, E.J. Delp, “A Printer Indexing System for Color Calibration with Applications in Dietary Assessment,” Proceeding of the International Conference on Image Analysis and Processing Workshop (ICIAP-W), Vol. 9281, Springer International, pp. 358-365, Aug 2015.

  64. Y. Wang, Y. He, F. Zhu, C.J. Boushey, E.J. Delp, “The Use of Temporal Information in Food Image Analysis,” Proceeding of the International Conference on Image Analysis and Processing Workshop (ICIAP-W), Vol. 9281, Springer International, pp. 317-325, Aug 2015.

  65. F. Zhu, M. Bosch, N. Khanna, C. J. Boushey, and E. J. Delp, “Multilevel Segmentation for Food Classification in Dietary AssessmentMultilevel Segmentation for Food Classification in Dietary Assessment,” Proceedings of 7th International Symposium on Image and Signal Processing and Analysis (ISPA), pp. 337-342, Dubrovnik, Croatia, Sep 2011.

  66. M. Yang, Y. He, F. Zhu, M. Bosch, M. Comer, and E.J. Delp, “Video Coding: Death Is Not Near,” Proceedings of the 53rd International Symposium ELMAR, pp. 85-88, Zadar, Croatia, Sep 2011. (Invited Paper).

  67. M. Bosch, F. Zhu, N. Khanna, C.J. Boushey, and E.J. Delp, “Combining Global and Local Features for Food Identification in Dietary Assessment,” Proceedings of the IEEE International Conference on Image Processing (ICIP), pp. 1789-1792, Brussels, Belgium, Sep 2011.

  68. M. Bosch, F. Zhu, N. Khanna, C.J. Boushey, and E.J. Delp, “Texture Descriptors Based on Fractal and Local Gradient Information Food Texture Descriptors Based on Fractal and Local Gradient Information,” Proceedings of the 19th European Signal Processing Conference (EUSIPCO), Barcelona, Spain, Aug 2011.

  69. M. Bosch, T. Schap, N. Khanna, F. Zhu, C.J. Boushey, and E.J. Delp, “Integrated Databases System for Mobile Dietary Assessment and Analysis,” Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6, Barcelona, Spain, Jul 2011.

  70. F. Zhu, M. Bosch, C. J. Boushey, and E. J. Delp, “An Image Analysis System for Dietary Assessment and Evaluation,” Proceedings of the IEEE International Conference on Image Processing (ICIP), pp. 1853-1856, Hong Kong, China, Sep 2010.

  71. M. Bosch, F. Zhu, and E. J. Delp, “Perceptual quality evaluation for texture and motion based video coding,” Proceedings of the IEEE International Conference on Image Processing (ICIP), pp. 2285-2288, Cairo, Egypt, Nov 2009.

  72. M. Bosch, F. Zhu, and E. J. Delp, “An Overview of Texture and Motion based Video Coding at Purdue University,” Proceedings of the 27th Picture Coding Symposium (PCS), pp. 1-4, Chicago, USA, May 2009.

  73. M. Bosch, F. Zhu, and E.J. Delp, “Video Coding Using Motion Classification,” Proceedings of the IEEE International Conference on Image Processing (ICIP), pp. 1588-1591, San Diego, USA, Oct 2008.

  74. M. Bosch, F. Zhu, and E.J. Delp, “Models for texture based video coding,” Proceedings of International Workshop on Local and Non-Local Approximation in Image Processing (LNLA), Lausanne, Switzerland, Aug 2008.

  75. F. Zhu, A. Mariappan, C.J. Boushey, D.A. Kerr, K.D. Lutes, D.S. Ebert, and E J. Delp, “Technology-Assisted Dietary Assessment," Proceedings of SPIE 6814, Computational Imaging VI, vol. 6814, pp. 681411-681411-10, San Jose, USA, Jan 2008.

  76. M. Bosch, F. Zhu, and E. J. Delp, “Spatial Texture Models for Video Compression,” Proceedings of IEEE International Conference on Image Processing (ICIP), pp. I-93-I-96, San Antonio, USA, Sep 2007.

  77. L. Liu, M. Bosch, F. Zhu, and E.J. Delp, “Recent advances in video compression: what's next?,” Proceedings of the IEEE International Symposium on Signal Processing and its Applications (ISSPA), pp. 1-8, Sharjah, United Arab Emirates, Feb 2007 (Plenary Paper).

  78. F. Zhu, K. Ng, G. Abdollahian, and E.J. Delp, “Spatial and Temporal Models for Texture-Based Video Coding,” Proceedings of SPIE 6508, Video Communications and Image Processing 2007 (VCIP), pp. 650806-650806-10, San Jose, USA, Jan 2007.

Patent

  1. E.J. Delp, H. Eicher-Miller, J. He, L. Lin, R. Mao, Z. Shao, S.K. Yarlagadda, F. Zhu, "Methods and Apparatus for Visual-Aware Hierarchy-Based Object Recognition,” Nov 11 2021, WO patent WO2021225842A1.

  2. F. Lv, F. Zhu, L. Zhou, and P. Wang, “Accurate 3D Finger Tracking with a Single Camera,” Apr 26 2016, US Patent 9323346.

  3. J. Ehmann, L. Zhou, O. G. Guleryuz, F. Lv, F. Zhu, and N. Dhar, “System and Method for Augmented Reality-Enabled Interactions and Collaboration,” Feb 23 2016, US Patent 9270943, World Patent 2016149616A1.

  4. F. Zhu, F. Lv, and P. Wang, “Augmented Video Calls on Mobile Devices,” Apr 21 2015, US Patent 9,013,536.

  5. Y. Bang, E.J. Delp, F. Zhu, H. Lee, and H. Choh, “Method and Apparatus for Enhancing Resolution of Video Image,” Dec 11 2012, US Patent 8331451.