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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 computer vision system for oocyte counting using images captured by smartphone
Celso Soares Costa, Everton Castel�ão Tetila, Gilberto Astolfi, et al.
Aquacultural Engineering (2019) Vol. 87, pp. 102017-102017
Closed Access | Times Cited: 25

Showing 25 citing articles:

Accuracy assessment of RFerns, NB, SVM, and kNN machine learning classifiers in aquaculture
Mustafa Çakır, Mesut Yılmaz, Mükerrem Atalay Oral, et al.
Journal of King Saud University - Science (2023) Vol. 35, Iss. 6, pp. 102754-102754
Open Access | Times Cited: 23
Weighing live sheep using computer vision techniques and regression machine learning
Diego André Sant’Ana, Marcio Carneiro Brito Pache, José Augusto Correa Martins, et al.
Machine Learning with Applications (2021) Vol. 5, pp. 100076-100076
Open Access | Times Cited: 37
A perspective on computer vision in biosensing
Li Liu, Ke Du
Biomicrofluidics (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 5
Best practices and current implementation of emerging smartphone-based (bio)sensors – Part 1: Data handling and ethics
Georgina M.S. Ross, Yunfeng Zhao, A.J. Bosman, et al.
TrAC Trends in Analytical Chemistry (2022) Vol. 158, pp. 116863-116863
Open Access | Times Cited: 20
Deep learning applied in fish reproduction for counting larvae in images captured by smartphone
Celso Soares Costa, Vanda Alice Garcia Zanoni, Lucimar Rodrigues Vieira Curvo, et al.
Aquacultural Engineering (2022) Vol. 97, pp. 102225-102225
Closed Access | Times Cited: 17
Shrimp egg counting with fully convolutional regression network and generative adversarial network
Junjie Zhang, Guowei Yang, Lihui Sun, et al.
Aquacultural Engineering (2021) Vol. 94, pp. 102175-102175
Closed Access | Times Cited: 20
Computer vision system for superpixel classification and segmentation of sheep
Diego André Sant’Ana, Marcio Carneiro Brito Pache, José Augusto Correa Martins, et al.
Ecological Informatics (2022) Vol. 68, pp. 101551-101551
Closed Access | Times Cited: 13
A new image dataset for the evaluation of automatic fingerlings counting
Vanir Garcia, Diego André Sant’Ana, Vanda Alice Garcia Zanoni, et al.
Aquacultural Engineering (2020) Vol. 89, pp. 102064-102064
Closed Access | Times Cited: 18
Machine learning and SLIC for Tree Canopies segmentation in urban areas
José Augusto Correa Martins, Geazy Vilharva Menezes, Wesley Nunes Gonçalves, et al.
Ecological Informatics (2021) Vol. 66, pp. 101465-101465
Closed Access | Times Cited: 14
Image dataset of urine test results on petri dishes for deep learning classification
Gabriel Rodrigues da Silva, Igor Batista Rosmaninho, Eduardo Zancul, et al.
Data in Brief (2023) Vol. 47, pp. 109034-109034
Open Access | Times Cited: 4
Use of computer vision to verify the viability of guavira seeds treated with tetrazolium salt
Higor Henrique Picoli Nucci, Riquiette Gomes de Azevedo, Mylena Corrêa Nogueira, et al.
Smart Agricultural Technology (2023) Vol. 5, pp. 100239-100239
Open Access | Times Cited: 4
Leveraging the feature distribution calibration and data augmentation for few-shot classification in fish counting
Jialong Zhou, Daxiong Ji, Jian Zhao, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108151-108151
Closed Access | Times Cited: 4
Counting, locating, and sizing of shrimp larvae based on density map regression
Chao Zhou, Guowei Yang, Lihui Sun, et al.
Aquaculture International (2023) Vol. 32, Iss. 3, pp. 3147-3168
Closed Access | Times Cited: 4
Identifying plant species in kettle holes using UAV images and deep learning techniques
José Augusto Correa Martins, José Marcato, Marlene Pätzig, et al.
Remote Sensing in Ecology and Conservation (2022) Vol. 9, Iss. 1, pp. 1-16
Open Access | Times Cited: 7
Learning-based low-illumination image enhancer for underwater live crab detection
Shuo Cao, Dean Zhao, Yueping Sun, et al.
ICES Journal of Marine Science (2020) Vol. 78, Iss. 3, pp. 979-993
Open Access | Times Cited: 9
Pervasive computing of adaptable recommendation system for head-up display in smart transportation
Ahmed Abu‐Khadrah, Muath Jarrah, Hamza Alrababah, et al.
Computers & Electrical Engineering (2022) Vol. 102, pp. 108204-108204
Closed Access | Times Cited: 6
Computer vision system for counting crustacean larvae by detection
Chen Rothschild, Eliahu D. Aflalo, Inbar Kedem, et al.
Smart Agricultural Technology (2023) Vol. 5, pp. 100289-100289
Open Access | Times Cited: 3
Overview of the application of computer vision technology in fish farming
Alexey Petrov, Anton Popov
E3S Web of Conferences (2020) Vol. 175, pp. 02015-02015
Open Access | Times Cited: 7
Developing Low-Cost Protocol for Counting and Measuring Eggs of Hilsa Fish (Tenualosa Ilisha)
Md Ahsan, Md Sayeed Abu Rayhan, Muhammad Yousuf Ali
(2024)
Closed Access
Multi-detector and motion prediction-based high-speed non-intrusive fingerling counting method
Jialong Zhou, Zhangying Ye, Jian Zhao, et al.
Biosystems Engineering (2024) Vol. 245, pp. 12-23
Closed Access
Image-Based Skin Cancer Early Detection using CNN Algorithm
Steven Johan, Friska Natalia, Ferry Vincenttius Ferdinand, et al.
(2021)
Closed Access | Times Cited: 1
Leveraging the Feature Distribution Calibration and Data Augmentation for Few-Shot Classification in Fish Counting
Jialong Zhou, Daxiong Ji, Jian Zhao, et al.
(2023)
Closed Access
Efectos de antibióticos en la biomasa, cobertura de área y clorofila de Lemna gibba y Azolla filiculoides
Ingrid Maldonado Jimenez, Jesús Miranda-Mamani, Yesica M. Mamani Arpasi
Revista de Investigaciones Altoandinas - Journal of High Andean Research (2023) Vol. 25, Iss. 4, pp. 233-240
Open Access
Fish Erythrocytes Nuclear Abnormalities Classification using Machine Learning
Newton Loebens, Bruno do Amaral Crispim, Nathalya Alice de Lima, et al.
(2023), pp. 96-101
Open Access
Automatic Counting Algorithm of Fry Based on Machine Vision System
Daxiong Ji, Jialong Zhou, Minghui Xu, et al.
(2021) Vol. 36, pp. 104-109
Closed Access
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