Agriculture-Vision Panel Discussion: Challenges and Opportunities


The 1st International Workshop and Prize Challenge on Agriculture-Vision

(official CVPR workshop website)
(dataset, papers)

Invited Talk 1: Scaling Spatio-Temporal Analytics — A Case in Agricultural Insights by IBM Research
by Dr. Sharath Pankanti @ IBM T.J. Watson Research Center

Invited Talk 2: Multi-modality Remote Sensing in High Throughput Phenotyping: Opportunities for Machine Learning
by Dr. Melba M. Crawford @ School of Civil Engineering and Department of Agronomy, Purdue University
Dr. Edward J. Delp @ School of Electrical and Computer Engineering, Purdue University

Invited Talk 3: Bridging Application and Research: Is agriculture just another application?
by Dr. Jennifer Hobbs
Director of Machine Learning @ Intelinair

Invited Talk 4: Improving Visual and Speech Recognition on Out-Domain Data
by Dr. Liangliang Cao @ Google Inc. & UMass

Invited Talk 5: Learning to Anticipate
by Prof. Alex Schwing @ UIUC

Invited Talk 6: Towards Understanding Agricultural Systems at Scale using Machine Learning
by Prof. Stefano Ermon @ Stanford University

Invited Talk 7: Interactive Object Segmentation with Inside-Outside Guidance
by Prof. Yunchao Wei @ UT Sydney

Invited Talk 8: Project FarmBeats: Aerial Mapping for Agricultural Farms and Beyond
by Dr. Sudipta N. Sinha, Principal Researcher @ Microsoft
Dr. Ranveer Chandra, Chief Scientist @ Microsoft Azure Global

Invited Talk 9: Enabling the African Farmer
by Prof. Munther Dahleh, Director, Institute of Data, Systems & Society @ MIT

Invited Talk 10: Learning using Limited Labels and Robust Multi-Modal Fusion
by Prof. Zsolt Kira @ Georgia Tech

—Panel Discussion—-
Industrial panelists:
@ IBM Research, Microsoft, Google X, Google Inc., Intelinair
Academic panelists:
@ MIT, Purdue, UIUC, University of Oregon, UTSydney, GaTech

Agriculture-Vision Panel Discussion: Challenges and Opportunities

—Oral Talks—-
All papers associated with oral/poster talks can be found here:


Oral 1: MSCG-Net with Adaptive Class Weighting Loss for Semantic Segmentation
by Qinghui Liu et. al. @ Norwegian Computing Center, Oslo & UiT Machine Learning Group

Oral 2: Finding Berries: Segmentation and Counting of Cranberries using Point Supervision and Shape Priors
by Peri Akiva et. al. @ Rutgers University

Oral 3: Visual 3D Reconstruction and Dynamic Simulation of Fruit Trees for Robotic Manipulation
by Francisco Yandun et. al. @ CMU

Oral 4: Cross-Regional Oil Palm Tree Detection
by Wenzhao Wu et. al. @ Tsinghua University & CUHK

Oral 5: Effective Data Fusion with Generalized Vegetation Index
by Hao Sheng et. al. @ Stanford University

Oral 6: Weakly Supervised Learning Guided by Activation Mapping Applied to a Novel Citrus Pest Benchmark
by Edson Bollis et. al. @ UNICAMP, Brazil

Oral 7: Fine-Grained Recognition in High-throughput Phenotyping
by Beichen Lyu @ Purdue University

Oral 8: Climate Adaptation: Reliably Predicting from Imbalanced Satellite Data
by Ruchit Rawal et. @ NSUT & Max Planck Institute for Intelligent Systems

—Challenge Talks—-
Talks related to the 1st Agriculture-Vision Prize Challenge
Agriculture-Vision Prize Challenge Results Summary
by Mang Tik Chiu et. al. @ UIUC

Challenge Talk 1: Residual DenseNet with Expert Network for Semantic Segmentatiom
by Hyunseong Park et. al. @ Agency for Defense Development, South Korea

Challenge Talk 2: MSCG-Net Models for The 1st Agriculture-Vision Challenge
by Qinghui Liu et. al. @ Norwegian Computing Center, Oslo & UiT Machine Learning Group

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