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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:

A comparison between Pixel-based deep learning and Object-based image analysis (OBIA) for individual detection of cabbage plants based on UAV Visible-light images
Zhangxi Ye, Kaile Yang, Yuwei Lin, et al.
Computers and Electronics in Agriculture (2023) Vol. 209, pp. 107822-107822
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Drones in vegetable crops: A systematic literature review
Marco Canicattì, Mariangela Vallone
Smart Agricultural Technology (2024) Vol. 7, pp. 100396-100396
Open Access | Times Cited: 25
Neuromorphic Computing for Smart Agriculture
Siyi Lu, Xinqing Xiao
Agriculture (2024) Vol. 14, Iss. 11, pp. 1977-1977
Open Access | Times Cited: 13
TSP-yolo-based deep learning method for monitoring cabbage seedling emergence
Xin Chen, Teng Liu, Kang Han, et al.
European Journal of Agronomy (2024) Vol. 157, pp. 127191-127191
Closed Access | Times Cited: 12
Comparison of different computer vision methods for vineyard canopy detection using UAV multispectral images
Massimo Vincenzo Ferro, Claus Aage Grøn Sørensen, Pietro Catania
Computers and Electronics in Agriculture (2024) Vol. 225, pp. 109277-109277
Open Access | Times Cited: 11
Crop Classification Combining Object-Oriented Method and Random Forest Model Using Unmanned Aerial Vehicle (UAV) Multispectral Image
Hui Deng, Wenjiang Zhang, Xiaoqian Zhang, et al.
Agriculture (2024) Vol. 14, Iss. 4, pp. 548-548
Open Access | Times Cited: 10
Enhanced recognition and counting of high-coverage Amorphophallus konjac by integrating UAV RGB imagery and deep learning
Ziyi Yang, Kunrong Hu, Weili Kou, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
A Multiscale Attention Segment Network-Based Semantic Segmentation Model for Landslide Remote Sensing Images
Nan Zhou, Jin Hong, Wenyu Cui, et al.
Remote Sensing (2024) Vol. 16, Iss. 10, pp. 1712-1712
Open Access | Times Cited: 8
Field cabbage detection and positioning system based on improved YOLOv8n
Ping Jiang, Aolin Qi, Jiao Zhong, et al.
Plant Methods (2024) Vol. 20, Iss. 1
Open Access | Times Cited: 8
A Combination of OBIA and Random Forest Based on Visible UAV Remote Sensing for Accurately Extracted Information about Weeds in Areas with Different Weed Densities in Farmland
Feng Chao, Wenjiang Zhang, Hui Deng, et al.
Remote Sensing (2023) Vol. 15, Iss. 19, pp. 4696-4696
Open Access | Times Cited: 16
Time-efficient low-resolution RGB aerial imaging for precision mapping of weed types in site-specific herbicide application
Lalita Panduangnat, Jetsada Posom, Kanda Runapongsa Saikaew, et al.
Crop Protection (2024) Vol. 184, pp. 106805-106805
Closed Access | Times Cited: 4
A Patch-Level Data Synthesis Pipeline Enhances Species-Level Crop and Weed Segmentation in Natural Agricultural Scenes
Tang Li, James Burridge, Pieter M. Blok, et al.
Agriculture (2025) Vol. 15, Iss. 2, pp. 138-138
Open Access
A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model
Kun Yang, Xiaohua Sun, Ruofan Li, et al.
Agronomy (2025) Vol. 15, Iss. 1, pp. 151-151
Open Access
Forecasting gaps in sugarcane fields containing weeds using low-resolution UAV imagery based on a machine-learning approach.
Wipawadee Thamoonlest, Jetsada Posom, Kanda Runapongsa Saikaew, et al.
Smart Agricultural Technology (2025), pp. 100780-100780
Open Access
Exploring the Efficacy of Python-Driven Automated Machine Vision Algorithms for Inspection in Sheet Metal Forming
S. Pratheesh Kumar, Nur Vidia Laksmi B.
Experimental Techniques (2025)
Closed Access
Lightweight highland barley detection based on improved YOLOv5
Minghui Cai, Hui Deng, Jianwei Cai, et al.
Plant Methods (2025) Vol. 21, Iss. 1
Open Access
Real-time detection of Chinese cabbage seedlings in the field based on YOLO11-CGB
Hang Shi, Changxi Liu, Miao Wu, et al.
Frontiers in Plant Science (2025) Vol. 16
Open Access
Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques
Rabiu Aminu, S. M. Cook, David Ljungberg, et al.
Artificial Intelligence in Agriculture (2025)
Open Access
Evaluating the Potential of Landsat 8/9 and Sentinel 2 Data and Different Spectral and Spatial Indices for Segment Extraction in Large Watersheds for OBIA Approach in Remote Sensing: A Case Study of the Sebou Watershed
Badia Ez-zahouani, Ana Cláudia Teodoro, Abdelhak El Kharki, et al.
Remote Sensing Applications Society and Environment (2025) Vol. 38, pp. 101575-101575
Closed Access
Changes in Land Use and Land Cover Patterns in Two Desert Basins Using Remote Sensing Data
Abdullah F. Alqurashi, Omar Alharbi
Geosciences (2025) Vol. 15, Iss. 5, pp. 178-178
Open Access
County-Level Poverty Evaluation Using Machine Learning, Nighttime Light, and Geospatial Data
Xiaoqian Zhang, Wenjiang Zhang, Hui Deng, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 962-962
Open Access | Times Cited: 3
Assessing the Potential of UAV for Large-Scale Fractional Vegetation Cover Mapping with Satellite Data and Machine Learning
Xunlong Chen, Yiming Sun, Xinyue Qin, et al.
Remote Sensing (2024) Vol. 16, Iss. 19, pp. 3587-3587
Open Access | Times Cited: 3
AI-Based UAV Swarms for Monitoring and Disease Identification of Brassica Plants Using Machine Learning: A Review
Zain Anwar Ali, Dingnan Deng, Muhammad Kashif Shaikh, et al.
Computer Systems Science and Engineering (2023) Vol. 48, Iss. 1, pp. 1-34
Open Access | Times Cited: 7
Potential of Lightweight Drones and Object-Oriented Image Segmentation in Forest Plantation Assessment
Jitendra Kumar Dixit, Ashok Kumar Bhardwaj, Saurabh Kumar Gupta, et al.
Remote Sensing (2024) Vol. 16, Iss. 9, pp. 1554-1554
Open Access | Times Cited: 2
Utilization of Improved Annotations From Object-Based Image Analysis as Training Data for DeepLab V3+ Model: A Focus on Road Extraction in Very High-Resolution Orthophotos
Sussi Sussi, Emir Husni, Rahadian Yusuf, et al.
IEEE Access (2024) Vol. 12, pp. 67910-67923
Open Access | Times Cited: 2
A novel multitask transformer deep learning architecture for joint classification and segmentation of horticulture plantations using very High-Resolution satellite imagery
P. V. Vinod, MD Behera, A. Jaya Prakash, et al.
Computers and Electronics in Agriculture (2024) Vol. 227, pp. 109540-109540
Closed Access | Times Cited: 2
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