| The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems J Jung, M Maeda, C Anjin, M Bhandari, A Ashapure, J Landivar Current Opinion in Biotechnology 70, 15-22, 2020 | 327 | 2020 |
| Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data A Ashapure, J Jung, A Chang, S Oh, J Yeom, M Maeda, A Maeda, N Dube, ... ISPRS Journal of Photogrammetry and Remote Sensing 169, 180-194, 2020 | 95 | 2020 |
| Comparison of Vegetation Indices Derived from UAV Data for Differentiation of Tillage Effects in Agriculture J Yeom, J Jung, A Chang, A Ashapure, M Maeda, A Maeda, J Landivar Remote Sensing 11 (13), 1548, 2019 | 94 | 2019 |
| A Comparative Study of RGB and Multispectral Sensor-Based Cotton Canopy Cover Modelling Using Multi-Temporal UAS Data A Ashapure, J Jung, A Chang, S Oh, M Maeda, J Landivar Remote Sensing 11 (23), 2757, 2019 | 85 | 2019 |
| Plant counting of cotton from UAS imagery using deep learning-based object detection framework S Oh, A Chang, A Ashapure, J Jung, N Dube, M Maeda, D Gonzalez, ... Remote Sensing 12 (18), 2981, 2020 | 68 | 2020 |
| A novel framework to detect conventional tillage and no-tillage cropping system effect on cotton growth and development using multi-temporal UAS data A Ashapure, J Jung, J Yeom, A Chang, M Maeda, A Maeda, J Landivar ISPRS Journal of Photogrammetry and Remote Sensing 152, 49-64, 2019 | 51 | 2019 |
| Unmanned aerial system based tomato yield estimation using machine learning A Ashapure, S Oh, TG Marconi, A Chang, J Jung, J Landivar, J Enciso Autonomous Air and Ground Sensing Systems for Agricultural Optimization and …, 2019 | 29 | 2019 |
| UAS based Tomato Yellow Leaf Curl Virus (TYLCV) disease detection system S Oh, A Ashapure, TG Marconi, J Jung, J Landivar Autonomous Air and Ground Sensing Systems for Agricultural Optimization and …, 2019 | 12 | 2019 |
| Tar spot disease quantification using unmanned aircraft systems (UAS) data S Oh, DY Lee, C Gongora-Canul, A Ashapure, J Carpenter, AP Cruz, ... Remote Sensing 13 (13), 2567, 2021 | 8 | 2021 |
| Segmentation-based classification of hyperspectral imagery using projected and correlation clustering techniques A Mehta, A Ashapure, O Dikshit Geocarto international 31 (10), 1045-1057, 2016 | 8 | 2016 |
| Application of unmanned aerial system for management of tomato cropping system TG Marconi, S Oh, A Ashapure, A Chang, J Jung, J Landivar, J Enciso Autonomous Air and Ground Sensing Systems for Agricultural Optimization and …, 2019 | 6 | 2019 |
| Landivar-BJ, The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems J Jung, M Maeda, A Chang, M Bhandari, A Ashapure Current Opinion in Biotechnology 70, 15-22, 2021 | 5 | 2021 |
| Unmanned aerial system genotype analysis using machine learning routines J Jung, J Landivar, M Maeda, A Ashapure US Patent App. 17/142,457, 2023 | 2 | 2023 |
| Combining UAS and Sentinel-2 Data to Estimate Canopy Parameters of a Cotton Crop Using Machine Learning A Ashapure, J Jung, S Oh, A Chang, N Dube, J Landivar IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 2 | 2020 |
| Towards Global Production of Water-quality Indicators in Support of SDG 6.3.2 N Pahlevan, N Golpayegani, A Radov, A Ashapure, W Wainwright American Geophysical Union, Fall Meeting 2019, abstract #GC25C-05, 2022 | 1 | 2022 |
| Estimation of Visual Rating of TAR Spot Disease of Corn Using Unmanned Aerial Systems (UAS) Data and Machine Learning Techniques S Oh, DY Lee, C Gongora-Canul, A Cruz-Sancan, A Ashapure, ... IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 1 | 2020 |
| Genotype Response to Irrigation Using an Unmanned Aircraft System Based High Throughput Phenotyping System J Landivar, J Jung, MM Maeda, N Dube, J McGinty, A Chang, A Ashapure, ... ASA, CSSA and SSSA International Annual Meetings (2019), 2019 | 1 | 2019 |
| Unmanned aerial system based cotton genotype selection using machine learning J Jung, A Ashapure, M Maeda, J Landivar, A Chang, J Yeom, S Hague, ... Autonomous Air and Ground Sensing Systems for Agricultural Optimization and …, 2018 | 1 | 2018 |
| Fluorescence microscopy image segmentation based on graph and fuzzy methods: A comparison with ensemble method M Beheshti, A Ashapure, M Rahnemoonfar, J Faichney Journal of Intelligent & Fuzzy Systems 34 (4), 2563-2578, 2018 | 1 | 2018 |
| Ensemble classifier based training data refinement technique for classification of remotely sensed optical images A Ashapure, A Mehta, O Dikshit, J Jung 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017 | 1 | 2017 |
Jinha JungPurdue UniversityVerified email at purdue.edu
