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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Fluorescence imaging for rapid monitoring of translocation behaviour of systemic markers in snap beans for automated crop/weed discrimination
Wen‐Hao Su, Steven A. Fennimore, David C. Slaughter
Biosystems Engineering (2019) Vol. 186, pp. 156-167
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Automatic Evaluation of Wheat Resistance to Fusarium Head Blight Using Dual Mask-RCNN Deep Learning Frameworks in Computer Vision
Wen‐Hao Su, JiaJing Zhang, Ce Yang, et al.
Remote Sensing (2020) Vol. 13, Iss. 1, pp. 26-26
Open Access | Times Cited: 106
Advanced Machine Learning in Point Spectroscopy, RGB- and Hyperspectral-Imaging for Automatic Discriminations of Crops and Weeds: A Review
Wen‐Hao Su
Smart Cities (2020) Vol. 3, Iss. 3, pp. 767-792
Open Access | Times Cited: 97
Proximal Methods for Plant Stress Detection Using Optical Sensors and Machine Learning
Alanna V. Zubler, Jeong‐Yeol Yoon
Biosensors (2020) Vol. 10, Iss. 12, pp. 193-193
Open Access | Times Cited: 88
Adsorption of rhodamine B on polyvinyl chloride, polystyrene, and polyethylene terephthalate microplastics in aqueous environments
Hailing Du, Yingshuang Zhang, Hongru Jiang, et al.
Environmental Technology & Innovation (2022) Vol. 27, pp. 102495-102495
Open Access | Times Cited: 58
SE-YOLOv5x: An Optimized Model Based on Transfer Learning and Visual Attention Mechanism for Identifying and Localizing Weeds and Vegetables
Jianlin Zhang, Wen‐Hao Su, Heyi Zhang, et al.
Agronomy (2022) Vol. 12, Iss. 9, pp. 2061-2061
Open Access | Times Cited: 40
Classification, uptake, translocation, and detection methods of nanoparticles in crop plants: a review
He-Yi Zhang, Wen‐Hao Su
Environmental Science Nano (2024) Vol. 11, Iss. 5, pp. 1847-1870
Closed Access | Times Cited: 14
Real-time lettuce-weed localization and weed severity classification based on lightweight YOLO convolutional neural networks for intelligent intra-row weed control
Rui Hu, Wen‐Hao Su, Jiale Li, et al.
Computers and Electronics in Agriculture (2024) Vol. 226, pp. 109404-109404
Closed Access | Times Cited: 13
Hyperspectral imaging and improved feature variable selection for automated determination of deoxynivalenol in various genetic lines of barley kernels for resistance screening
Wen‐Hao Su, Ce Yang, Yanhong Dong, et al.
Food Chemistry (2020) Vol. 343, pp. 128507-128507
Open Access | Times Cited: 56
Evaluation of different deep convolutional neural networks for detection of broadleaf weed seedlings in wheat
Jiayao Zhuang, Xuehan Li, Muthukumar Bagavathiannan, et al.
Pest Management Science (2021) Vol. 78, Iss. 2, pp. 521-529
Closed Access | Times Cited: 46
Imaging Spectroscopy and Machine Learning for Intelligent Determination of Potato and Sweet Potato Quality
Wen‐Hao Su, Huidan Xue
Foods (2021) Vol. 10, Iss. 9, pp. 2146-2146
Open Access | Times Cited: 40
Automatic Localization of Soybean Seedlings Based on Crop Signaling and Multi-View Imaging
Bo Jiang, He-Yi Zhang, Wen‐Hao Su
Sensors (2024) Vol. 24, Iss. 10, pp. 3066-3066
Open Access | Times Cited: 6
Semi-supervised learning for detection of sedges in sod farms
Xin Chen, Teng Liu, Kang Han, et al.
Crop Protection (2024) Vol. 179, pp. 106626-106626
Closed Access | Times Cited: 5
Key Technologies of Intelligent Weeding for Vegetables: A Review
Jinkang Jiao, Ying Zang, Chaowen Chen
Agriculture (2024) Vol. 14, Iss. 8, pp. 1378-1378
Open Access | Times Cited: 5
Crop signal markers facilitate crop detection and weed removal from lettuce and tomato by an intelligent cultivator
HannahJoy Kennedy, Steven A. Fennimore, David C. Slaughter, et al.
Weed Technology (2019) Vol. 34, Iss. 3, pp. 342-350
Open Access | Times Cited: 31
Seedling Growth and Systemic Uptake of Liquid Vermicompost-Coated Seeds in Organic Pumpkin (Cucurbita sp.)
W. Pola, Sukanya Aiamla-or
Horticulturae (2025) Vol. 11, Iss. 1, pp. 58-58
Open Access
Automatic visualization of crop signaling markers in tomato plants for differentiation of labeled plants from weeds based on fluorescence imaging
He-Yi Zhang, Wen‐Hao Su, Bo Jiang, et al.
Computers and Electronics in Agriculture (2025) Vol. 231, pp. 110009-110009
Closed Access
Systemic Uptake of Rhodamine Tracers Quantified by Fluorescence Imaging: Applications for Enhanced Crop–Weed Detection
Yu Jiang, Masoume Amirkhani, Ethan Lewis, et al.
AgriEngineering (2025) Vol. 7, Iss. 3, pp. 49-49
Open Access
Non-destructive evaluation of photostability of crop signaling compounds and dose effects on celery vigor for precision plant identification using computer vision
Wen‐Hao Su, David C. Slaughter, Steven A. Fennimore
Computers and Electronics in Agriculture (2019) Vol. 168, pp. 105155-105155
Open Access | Times Cited: 26
Crop plant signaling for real-time plant identification in smart farm: A systematic review and new concept in artificial intelligence for automated weed control
Wen‐Hao Su
Artificial Intelligence in Agriculture (2020) Vol. 4, pp. 262-271
Open Access | Times Cited: 26
Non-destructive methods for detection of food quality
Maimunah Mohd Ali, Norhashila Hashim
Elsevier eBooks (2022), pp. 645-667
Closed Access | Times Cited: 16
Development of a systemic crop signalling system for automated real-time plant care in vegetable crops
Wen‐Hao Su, Steven A. Fennimore, David C. Slaughter
Biosystems Engineering (2020) Vol. 193, pp. 62-74
Open Access | Times Cited: 23
Recognition of Drought Stress State of Tomato Seedling Based on Chlorophyll Fluorescence Imaging
Long Yan, Minjuan Ma
IEEE Access (2022) Vol. 10, pp. 48633-48642
Open Access | Times Cited: 11
Drought stress impact on the performance of deep convolutional neural networks for weed detection in Bahiagrass
Jiayao Zhuang, Xiaojun Jin, Yong Chen, et al.
Grass and Forage Science (2022) Vol. 78, Iss. 1, pp. 214-223
Closed Access | Times Cited: 11
Systemic Uptake of Fluorescent Tracers by Soybean (Glycine max (L.) Merr.) Seed and Seedlings
Zhen Wang, Masoume Amirkhani, Suemar Alexandre Gonçalves Avelar, et al.
Agriculture (2020) Vol. 10, Iss. 6, pp. 248-248
Open Access | Times Cited: 16
Development of a Three-Dimensional Plant Localization Technique for Automatic Differentiation of Soybean from Intra-Row Weeds
Wen‐Hao Su, Ji Sheng, Qing-Yang Huang
Agriculture (2022) Vol. 12, Iss. 2, pp. 195-195
Open Access | Times Cited: 9
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