Program
MLCAS 2018 (Oct 24th 2018, 14:30 – 18:30)
14:30 to 14:35 - Introduction: Prof. Soumik Sarkar, Iowa Sate University.
14:35 to 15:05 - Keynote 1: Dr. Parag Chitnis, USDA NIFA.
15:05 to 15:30 - Keynote 2: Prof. Vineeth N Balasubramanian, IIT Hyderabad.
15:30 to 16:00 - Contributed Talks 1 (Chaired by Prof. Wei Guo): (15 min X 2)
Talk 1: Feasibility of dimensionality reduction and reconstruction of occluded plants using generative deep networks (University of Illinois at Urbana Champaign)
Authors: Anwesa Choudhuri and Girish Chowdhary
Talk 2: Data-Farm for agricultural big data and AI applications (University of Tokyo)
Authors: Masayuki Hirafuji, Wei Guo, Seishi Ninomiya, Tokihiro Fukatsu, Takuji Kiura, Atsushi Ito, Kazunori Taguchi, Seishi Ikeda, Koichi Nagasawa and Masahiro Okada
16:00 to 16:30 - Break and Poster session.
16:30 to 16:55 - Keynote 3: Prof. Seishi Ninomiya, University of Tokyo.
16:55 to 17:55 - Contributed Talks 2 (Chaired by Prof. Baskar Ganapathysubramanian ): (15 min X 4)
Talk 3: An Understandable DCNN Framework for Soybean Stress Phenotyping (Iowa State University)
Authors: David Blystone, Sambuddha Ghosal, Asheesh Singh, Baskar Ganapathysubramanian, Arti Singh and Soumik Sarkar
Talk 4: Predicting Heading Dates of Rice Using the Integrated Approach Combining Machine Learning Method and Crop Model (University of Tokyo)
Authors: Tai-Shen Chen and Hiroyoshi Iwata
Talk 5: Using Machine Learning with Side Facing Camera Data on a Compact Agbot to Estimate Weed Density (University of Illinois at Urbana Champaign)
Authors: Wyatt McAllister, Denis Osipychev, Zhongzhong Zhang, Joshua Varghese, Girish Chowdhary and Adam Davis
Talk 6: Integrating genotype and weather variables for soybean yield prediction using deep learning (Iowa State University)
Authors: Johnathon Shook, Linjiang Wu, Tryambak Gangopadhyay, Baskar Ganapathysubramanian, Soumik Sarkar and Asheesh Singh .
17:55 to 18:00 - Conclusion: Prof. Baskar Ganapathysubramanian
18:00 to 18:30 - Break and Poster session
Accepted Posters:
1. A real-time deep-learning based phenotyping framework for tomato detection and ripeness estimation (University of Tokyo)
Authors: Yue Mu, Taishen Chen, Seishi Ninomiya and Wei Guo
2. Optimization of multi-environment trial for genomic selection (University of Tokyo)
Authors: Ryokei Tanaka and Hiroyoshi Iwata
3. Automated Counting of Filled and Unfilled Spikelets of Aerobic Rice Using Blue Channel Discrimination (IIT Hyderabad)
Authors: Ajay Kumar, Bharath Ramakrishna, Mahesh Taparia, P Rajalakshmi, Balram Marathi and U.B. Desai
4. Deep Learning Based Plant Disease Diagnosis for Grape Plant (GGSIP, New Delhi)
Authors: Shradha Verma, Anuradha Chug, Amit Prakash Singh, Puranjay Rajvanshi and Shubham Sharma
5. Robot-based Corn Stand Counting using Deep Learning (University of Illinois at Urbana Champaign)
Authors: Zhongzhong Zhang and Girish Chowdhary
6. A Label Efficient Deep Learning Framework for Sorghum Head Detection and Counting (Iowa State University/ Queensland Alliance for Agriculture and Food Innovation/University of Tokyo)
Authors: Sambuddha Ghosal, Bangyou Zheng, Scott Chapman, Andries Potgieter, David Jordan, Xuemin Wang, Asheesh Singh, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar and Wei Guo
7. Hyperspectral super-resolution by residual neural networks (Iowa State University)
Authors: Koushik Nagasubramanian, David Blystone, Asheesh Singh, Arti Singh, Baskar Ganapathysubramanian and Soumik Sarkar