| Deep learning for smart agriculture: Concepts, tools, applications, and opportunities N Zhu, X Liu, Z Liu, K Hu, Y Wang, J Tan, M Huang, Q Zhu, X Ji, Y Jiang, ... International Journal of Agricultural and Biological Engineering 11 (4), 32-44, 2018 | 227 | 2018 |
| Image texture features as indicators of beef tenderness J Li, J Tan, FA Martz, H Heymann meat science 53 (1), 17-22, 1999 | 226 | 1999 |
| Beef marbling and color score determination by image processing DE Gerrard, X Gao, J Tan Journal of food science 61 (1), 145-148, 1996 | 226 | 1996 |
| Detection of incomplete ellipse in images with strong noise by iterative randomized Hough transform (IRHT) W Lu, J Tan Pattern Recognition 41 (4), 1268-1279, 2008 | 225 | 2008 |
| Evaluation of pork color by using computer vision J Lu, J Tan, P Shatadal, DE Gerrard Meat science 56 (1), 57-60, 2000 | 224 | 2000 |
| Meat quality evaluation by computer vision J Tan Journal of food engineering 61 (1), 27-35, 2004 | 206 | 2004 |
| Classification of tough and tender beef by image texture analysis J Li, J Tan, P Shatadal Meat science 57 (4), 341-346, 2001 | 186 | 2001 |
| Automated fetal head detection and measurement in ultrasound images by iterative randomized Hough transform W Lu, J Tan, R Floyd Ultrasound in medicine & biology 31 (7), 929-936, 2005 | 132 | 2005 |
| Ultrasound speckle reduction by a SUSAN-controlled anisotropic diffusion method J Yu, J Tan, Y Wang Pattern recognition 43 (9), 3083-3092, 2010 | 120 | 2010 |
| Prediction of dissolved oxygen in a fishery pond based on gated recurrent unit (GRU) W Li, H Wu, N Zhu, Y Jiang, J Tan, Y Guo Information Processing in Agriculture 8 (1), 185-193, 2021 | 118 | 2021 |
| Recent Advances in the Application of Chlorophyll a Fluorescence from Photosystem II Y Guo, J Tan Photochemistry and photobiology 91 (1), 1-14, 2015 | 109 | 2015 |
| Analysis of expanded‐food texture by image processing part I: Geometric properties X Gao, J Tan Journal of Food Process Engineering 19 (4), 425-444, 1996 | 71 | 1996 |
| Global research trends in food safety in agriculture and industry from 1991 to 2018: A data-driven analysis K Hu, J Liu, B Li, L Liu, SMT Gharibzahedi, Y Su, Y Jiang, J Tan, Y Wang, ... Trends in Food Science & Technology 85, 262-276, 2019 | 64 | 2019 |
| Identifying damaged soybeans by color image analysis. P Shatadal, J Tan | 64 | 2003 |
| Acoustic wave analysis for food crispness evaluation X Liu, J Tan Journal of Texture Studies 30 (4), 397-408, 1999 | 49 | 1999 |
| A kinetic model structure for delayed fluorescence from plants Y Guo, J Tan Biosystems 95 (2), 98-103, 2009 | 42 | 2009 |
| Mechanically recovered neck bone lean and ascorbic acid improve color stability of ground beef patties BP Demos, DE Gerrard, RW Mandigo, X Gao, J Tan Journal of food science 61 (3), 656-659, 1996 | 40 | 1996 |
| Modeling and simulation of the initial phases of chlorophyll fluorescence from Photosystem II Y Guo, J Tan BioSystems 103 (2), 152-157, 2011 | 35 | 2011 |
| Predicting beef tenderness from image texture features J Li, J Tan, FA Martz 1997 ASAE annual international meeting technical papers, paper, 49085-9659, 1997 | 35 | 1997 |
| Prediction of dissolved oxygen concentration in aquatic systems based on transfer learning N Zhu, X Ji, J Tan, Y Jiang, Y Guo Computers and Electronics in Agriculture 180, 105888, 2021 | 33 | 2021 |
Kevin A JanniProfessor, University of MinnesotaVerified email at umn.edu
