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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 New Belt Ore Image Segmentation Method Based on the Convolutional Neural Network and the Image-Processing Technology
Xiqi Ma, Pengyu Zhang, Xiaofei Man, et al.
Minerals (2020) Vol. 10, Iss. 12, pp. 1115-1115
Open Access | Times Cited: 24

Showing 24 citing articles:

Efficient image segmentation based on deep learning for mineral image classification
Yang Liu, Zelin Zhang, Xiang Liu, et al.
Advanced Powder Technology (2021) Vol. 32, Iss. 10, pp. 3885-3903
Closed Access | Times Cited: 126
Deep learning implementations in mining applications: a compact critical review
Faris Azhari, Charlotte Sennersten, Craig A. Lindley, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. 12, pp. 14367-14402
Open Access | Times Cited: 17
Deep learning in image segmentation for mineral production: A review
Yang Liu, Xueyi Wang, Zelin Zhang, et al.
Computers & Geosciences (2023) Vol. 180, pp. 105455-105455
Closed Access | Times Cited: 16
An Improved Boundary-Aware U-Net for Ore Image Semantic Segmentation
Wei Wang, Qing Li, Xiao Chengyong, et al.
Sensors (2021) Vol. 21, Iss. 8, pp. 2615-2615
Open Access | Times Cited: 38
Roping Prediction Versus Detection: Could Prediction Be Possible?
Lin Yang, Lei Chen, Difan Tang, et al.
Minerals (2025) Vol. 15, Iss. 2, pp. 110-110
Open Access
Efficient and Lightweight Framework for Real-Time Ore Image Segmentation Based on Deep Learning
Guodong Sun, Delong Huang, Le Cheng, et al.
Minerals (2022) Vol. 12, Iss. 5, pp. 526-526
Open Access | Times Cited: 17
Review of deep learning approaches in solving rock fragmentation problems
Mikhail Ronkin, Elena N. Akimova, Vladimir E. Misilov
AIMS Mathematics (2023) Vol. 8, Iss. 10, pp. 23900-23940
Open Access | Times Cited: 8
DDR-Unet: A High-Accuracy and Efficient Ore Image Segmentation Method
Fei Li, Xiaoyan Liu, Yufeng Yin, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-20
Closed Access | Times Cited: 7
Image Process of Rock Size Distribution Using DexiNed-Based Neural Network
Haijie Li, Gauti Asbjörnsson, Mats Lindqvist
Minerals (2021) Vol. 11, Iss. 7, pp. 736-736
Open Access | Times Cited: 15
Online techniques for performance and condition monitoring of hydrocyclone: present status and the future
Shankar Prasad Mishra, A. K. Majumder
Mineral Processing and Extractive Metallurgy Review (2022) Vol. 44, Iss. 4, pp. 281-296
Closed Access | Times Cited: 9
Hardware and Software Solutions for the Generation of a Database of HSV-Color Characteristics for the Main Ores and Rocks of the Khibiny Massif
D. N. Shibaeva, Roman Pavlovich Voronin, A. A. Kompanchenko, et al.
Minerals (2024) Vol. 14, Iss. 2, pp. 186-186
Open Access | Times Cited: 1
Creep Characteristics Research of Ultra-deep Composite Rock Salt in Tarim Basin Based on 2D Image Contour Identification
Yingtong Ju, Mian Chen, Yunhu Lu
Rock Mechanics and Rock Engineering (2024) Vol. 57, Iss. 8, pp. 5663-5683
Closed Access | Times Cited: 1
Superpixel-Based Grain Segmentation in Sandstone Thin-Section
Przemysław Dąbek, Krzysztof Chudy, Izabella Nowak, et al.
Minerals (2023) Vol. 13, Iss. 2, pp. 219-219
Open Access | Times Cited: 3
Synthetic Image Generation for Visual Particle Size Distribution Estimation based on U-NET Convolutional Networks
Akshay Chavan, Antonius Schmidt, Hendrik Klopries, et al.
(2023), pp. 336-341
Closed Access | Times Cited: 3
Packaging Beautification Design Based on Visual Image and Personalized Pattern Matching
Deli Chen
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 2
Open Access
Image-based fragment size distribution analysis of muck pile using multiple spherical scales for improving accuracy and safety
Jieun Baek, Yosoon Choi
Measurement (2024), pp. 115776-115776
Closed Access
All-weather real-time ore detection method based on near-infrared structured light and zero-crossing points characteristics
K. Tian, Hanyu Hong, Xun Zhang, et al.
Measurement (2023) Vol. 222, pp. 113628-113628
Closed Access | Times Cited: 1
Estimation of Final Product Concentration in Metalic Ores Using Convolutional Neural Networks
Jakub Progorowicz, Artur Skoczylas, Sergii Anufriiev, et al.
Minerals (2022) Vol. 12, Iss. 12, pp. 1480-1480
Open Access | Times Cited: 1
VBM granulometry for real applications in the fertilizer industry
Nelson de F. Traversi, Douglas Alves Goulart, Julio Cezar O. Mendonça, et al.
(2021), pp. 276-281
Closed Access | Times Cited: 1
Designing the system for detecting unsuitable marble stones for an industrial process using convolutional neural networks
Shubin Ivan, Denis Shilin
2022 4th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE) (2023), pp. 1-6
Closed Access
Detection of Oversized Objects in a Video Stream Using an Image Classification with Deep Neural Networks
Przemysław Jamontt, Juliusz Sarna, Jakub Wnuk, et al.
Lecture notes in networks and systems (2023), pp. 95-104
Closed Access
Multi-Task Decoupled Convolutional Neural Network for Efficient Segmentation of Densely Distributed Coal and Gangue
Huajie Liu, Ke Xu
(2023)
Closed Access
Advanced Techniques and Efficiency Assessment of Mechanical Processing
D. Saramak, Marek Pawełczyk, Tomasz Niedoba
MDPI eBooks (2022)
Open Access
Special Issue “Advanced Techniques and Efficiency Assessment of Mechanical Processing”—Editorial Note and Critical Review of the Problems
D. Saramak
Minerals (2021) Vol. 11, Iss. 12, pp. 1428-1428
Open Access
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