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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:

Hyperspectral fruit and vegetable classification using convolutional neural networks
Jan Steinbrener, Konstantin Posch, Raimund Leitner
Computers and Electronics in Agriculture (2019) Vol. 162, pp. 364-372
Closed Access | Times Cited: 130

Showing 1-25 of 130 citing articles:

A Review of Convolutional Neural Network Applied to Fruit Image Processing
José Naranjo-Torres, Marco Mora, Ruber Hernández-García, et al.
Applied Sciences (2020) Vol. 10, Iss. 10, pp. 3443-3443
Open Access | Times Cited: 305
Deep learning in food category recognition
Yudong Zhang, Lijia Deng, Hengde Zhu, et al.
Information Fusion (2023) Vol. 98, pp. 101859-101859
Open Access | Times Cited: 239
Efficient extraction of deep image features using convolutional neural network (CNN) for applications in detecting and analysing complex food matrices
Yao Liu, Hongbin Pu, Da‐Wen Sun
Trends in Food Science & Technology (2021) Vol. 113, pp. 193-204
Closed Access | Times Cited: 231
A review of deep learning used in the hyperspectral image analysis for agriculture
Chunying Wang, Baohua Liu, Lipeng Liu, et al.
Artificial Intelligence Review (2021) Vol. 54, Iss. 7, pp. 5205-5253
Closed Access | Times Cited: 198
Real-time hyperspectral imaging for the in-field estimation of strawberry ripeness with deep learning
Zongmei Gao, Yuanyuan Shao, Guantao Xuan, et al.
Artificial Intelligence in Agriculture (2020) Vol. 4, pp. 31-38
Open Access | Times Cited: 140
Recent Advancements in Fruit Detection and Classification Using Deep Learning Techniques
Chiagoziem C. Ukwuoma, Qin Zhi-guang, Md Belal Bin Heyat, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-29
Open Access | Times Cited: 110
Applications of machine learning techniques for enhancing nondestructive food quality and safety detection
Yuandong Lin, Ji Ma, Qijun Wang, et al.
Critical Reviews in Food Science and Nutrition (2022) Vol. 63, Iss. 12, pp. 1649-1669
Closed Access | Times Cited: 95
Optimization strategies of fruit detection to overcome the challenge of unstructured background in field orchard environment: a review
Yunchao Tang, Jiajun Qiu, Yunqi Zhang, et al.
Precision Agriculture (2023) Vol. 24, Iss. 4, pp. 1183-1219
Closed Access | Times Cited: 86
Recent advances and applications of artificial intelligence and related technologies in the food industry
Addanki Mounika, Priyanka Patra, Prameela Kandra
Applied Food Research (2022) Vol. 2, Iss. 2, pp. 100126-100126
Closed Access | Times Cited: 70
A review on the combination of deep learning techniques with proximal hyperspectral images in agriculture
Jayme Garcia Arnal Barbedo
Computers and Electronics in Agriculture (2023) Vol. 210, pp. 107920-107920
Closed Access | Times Cited: 62
DenseNet-201 and Xception Pre-Trained Deep Learning Models for Fruit Recognition
Farsana Salim, Faisal Saeed, Shadi Basurra, et al.
Electronics (2023) Vol. 12, Iss. 14, pp. 3132-3132
Open Access | Times Cited: 50
A research review on deep learning combined with hyperspectral Imaging in multiscale agricultural sensing
Luyu Shuai, Zhiyong Li, Ziao Chen, et al.
Computers and Electronics in Agriculture (2024) Vol. 217, pp. 108577-108577
Closed Access | Times Cited: 34
Fruit and vegetable disease detection and classification: Recent trends, challenges, and future opportunities
Sachin Kumar Gupta, Ashish Kumar Tripathi
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108260-108260
Closed Access | Times Cited: 17
Intelligent food processing: Journey from artificial neural network to deep learning
Janmenjoy Nayak, Kanithi Vakula, Paidi Dinesh, et al.
Computer Science Review (2020) Vol. 38, pp. 100297-100297
Closed Access | Times Cited: 111
Analysis of Artificial Intelligence based Image Classification Techniques
Subarna Shakya
Journal of Innovative Image Processing (2020) Vol. 2, Iss. 1, pp. 44-54
Open Access | Times Cited: 106
Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat
Mahmoud Al-Sarayreh, Marlon M. Reis, Wei Qi Yan, et al.
Food Control (2020) Vol. 117, pp. 107332-107332
Closed Access | Times Cited: 102
Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images
Antonio Fazari, Óscar J. Pellicer-Valero, Juan Gómez‐Sanchís, et al.
Computers and Electronics in Agriculture (2021) Vol. 187, pp. 106252-106252
Open Access | Times Cited: 84
Machine vision for the maturity classification of oil palm fresh fruit bunches based on color and texture features
Anindita Septiarini, Andi Sunyoto, Hamdani Hamdani, et al.
Scientia Horticulturae (2021) Vol. 286, pp. 110245-110245
Closed Access | Times Cited: 82
A novel method based on machine vision system and deep learning to detect fraud in turmeric powder
Ahmad Jahanbakhshi, Yousef Abbaspour‐Gilandeh, Kobra Heidarbeigi, et al.
Computers in Biology and Medicine (2021) Vol. 136, pp. 104728-104728
Closed Access | Times Cited: 71
Advances in infrared spectroscopy and hyperspectral imaging combined with artificial intelligence for the detection of cereals quality
Dong An, Liu Zhang, Zhe Liu, et al.
Critical Reviews in Food Science and Nutrition (2022) Vol. 63, Iss. 29, pp. 9766-9796
Closed Access | Times Cited: 57
Waste management using an automatic sorting system for carrot fruit based on image processing technique and improved deep neural networks
Ahmad Jahanbakhshi, Mohammad Momeny, Majid Mahmoudi, et al.
Energy Reports (2021) Vol. 7, pp. 5248-5256
Open Access | Times Cited: 55
Recent advances in shelf life prediction models for monitoring food quality
Fangchao Cui, Shiwei Zheng, Dangfeng Wang, et al.
Comprehensive Reviews in Food Science and Food Safety (2023) Vol. 22, Iss. 2, pp. 1257-1284
Closed Access | Times Cited: 35
Current advances in imaging spectroscopy and its state-of-the-art applications
Anam Zahra, Rizwan Qureshi, Muhammad Sajjad, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 122172-122172
Open Access | Times Cited: 22
Vision-based fruit recognition via multi-scale attention CNN
Weiqing Min, Zhiling Wang, Jiahao Yang, et al.
Computers and Electronics in Agriculture (2023) Vol. 210, pp. 107911-107911
Closed Access | Times Cited: 21
Convolutional neural network ensemble learning for hyperspectral imaging-based blackberry fruit ripeness detection in uncontrolled farm environment
Chollette C. Olisah, Ben Trewhella, Bo Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 132, pp. 107945-107945
Open Access | Times Cited: 11
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