Most cited papers in Currency Recognition and Detection
What are the most cited papers in Currency Recognition and Detection?
The most cited paper in Currency Recognition and Detection is "Deep learning in agriculture: A survey" (Andreas Kamilaris, Francesc Xavier Prenafeta-Boldú, 2018), with 5,070 citations. Next come "Deep learning and its applications to machine health monitoring" (2,854) and "Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions" (2,558).
Showing 50 of 100 papers. Every paper with more than 224 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Deep learning in agriculture: A survey Andreas Kamilaris, Francesc Xavier Prenafeta-Boldú · Computers and Electronics in Agriculture | 22 Feb 2018 | 5,070 |
| 2 | Deep learning and its applications to machine health monitoring Rui Zhao, Ruqiang Yan, Zhenghua Chen et al. · Mechanical Systems and Signal Processing | 14 Jun 2018 | 2,854 |
| 3 | Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions Iqbal H. Sarker · SN Computer Science | 18 Aug 2021 | 2,558 |
| 4 | Activation functions in deep learning: A comprehensive survey and benchmark Shiv Ram Dubey, Satish Kumar Singh, B.B. Chaudhuri · Neurocomputing | 3 Jul 2022 | 1,226 |
| 5 | A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning Shaveta Dargan, Munish Kumar, Maruthi Rohit Ayyagari et al. · Archives of Computational Methods in Engineering | Jun 2019 | 1,213 |
| 6 | A deep learning framework for financial time series using stacked autoencoders and long-short term memory Wei Bao, Jun Yue, Yulei Rao · PLoS ONE | 14 Jul 2017 | 1,135 |
| 7 | Analysis of Dimensionality Reduction Techniques on Big Data Thippa Reddy Gadekallu, Praveen Kumar Reddy Maddikunta, Kuruva Lakshmanna et al. · IEEE Access | 2020 | 886 |
| 8 | Modern Trends in Hyperspectral Image Analysis: A Review Muhammad Jaleed Khan, Hamid Saeed Khan, Adeel Yousaf et al. · IEEE Access | 2018 | 879 |
| 9 | A CNN–LSTM model for gold price time-series forecasting Ioannis E. Livieris, Emmanuel G. Pintelas, Panagiotis Pintelas · Neural Computing and Applications | 13 Apr 2020 | 875 |
| 10 | A Review of Machine Learning and Deep Learning Applications Pramila P. Shinde, Seema Shah | Aug 2018 | 761 |
| 11 | Edge Detection Techniques - An Overview Djemel Ziou, Salvatore Tabbone | 1998 | 760 |
| 12 | Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition Oludare Isaac Abiodun, Muhammad Ubale Kiru, Aman Jantan et al. · IEEE Access | 2019 | 756 |
| 13 | Conceptual Understanding of Convolutional Neural Network- A Deep Learning Approach Sakshi Indolia, Anil Kumar Goswami, Sourav Mishra et al. · Procedia Computer Science | 2018 | 751 |
| 14 | Classification Archaeological Fragments into Groups Nada Abdullah Rasheed, Md Jan Nordin, Awfa Hasan Dakheel et al. · Research Journal of Applied Sciences Engineering and Technology | 15 Sep 2017 | 717 |
| 15 | Financial time series forecasting model based on CEEMDAN and LSTM Jian Feng Cao, Zhi Li, Jian Li · Physica A Statistical Mechanics and its Applications | 13 Dec 2018 | 717 |
| 16 | Computer vision technology in agricultural automation —A review Hongkun Tian, Tianhai Wang, Yadong Liu et al. · Information Processing in Agriculture | 27 Sep 2019 | 687 |
| 17 | Convolutional Neural Network (CNN) for Image Detection and Recognition Rahul Singh Chauhan, Kamal Kumar Ghanshala, Rakesh Chandra Joshi · 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) | Dec 2018 | 673 |
| 18 | Computer Vision and Pattern Recognition 2020 Zeynep Akata, Andreas Geiger, Torsten Sattler · International Journal of Computer Vision | 15 Oct 2021 | 647 |
| 19 | Detecting and reading text in natural scenes Xiang-Rong Chen, Alan Yuille | 12 Nov 2004 | 632 |
| 20 | Fruits and vegetables quality evaluation using computer vision: A review Anuja Bhargava, Atul Bansal · Journal of King Saud University - Computer and Information Sciences | 5 Jun 2018 | 624 |
| 21 | Rewrite the Stars Xu Ma, Xiyang Dai, Yue Bai et al. | 16 Jun 2024 | 604 |
| 22 | A review of object detection based on deep learning Youzi Xiao, Zhiqiang Tian, Jiachen Yu et al. · Multimedia Tools and Applications | 12 Jun 2020 | 583 |
| 23 | Object Detection in 20 Years: A Survey Zhengxia Zou, Chen, Keyan, Zhenwei Shi et al. · arXiv (Cornell University) | 13 May 2019 | 562 |
| 24 | Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time Serkan Ayvaz, Koray Alpay · Expert Systems with Applications | 18 Jan 2021 | 548 |
| 25 | Feature Extraction using Convolution Neural Networks (CNN) and Deep Learning Manjunath Jogin, Mohana, M S Madhulika et al. | May 2018 | 530 |
| 26 | A Survey on Blockchain Technology: Evolution, Architecture and Security Muhammad Nasir Mumtaz Bhutta, Amir Ali Khwaja, Adnan Nadeem et al. · IEEE Access | 2021 | 525 |
| 27 | Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis Elie I. Bouri, Syed Jawad Hussain Shahzad, David Roubaud et al. · The Quarterly Review of Economics and Finance | 31 Mar 2020 | 524 |
| 28 | Motor Anomaly Detection for Unmanned Aerial Vehicles Using Reinforcement Learning Huimin Lu, Yujie Li, Shenglin Mu et al. · IEEE Internet of Things Journal | 8 Aug 2017 | 507 |
| 29 | Im2Calories: Towards an Automated Mobile Vision Food Diary Austin Myers, Nick Johnston, Vivek Rathod et al. | Dec 2015 | 507 |
| 30 | Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm Zeinab Arabasadi, Roohallah Alizadehsani, Mohamad Roshanzamir et al. · Computer Methods and Programs in Biomedicine | 18 Jan 2017 | 505 |
| 31 | An innovative neural network approach for stock market prediction Xiongwen Pang, Yanqiang Zhou, Pan Wang et al. · The Journal of Supercomputing | 12 Jan 2018 | 479 |
| 32 | Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing Liangzhi Li, Kaoru Ota, Mianxiong Dong · IEEE Transactions on Industrial Informatics | Jun 2018 | 473 |
| 33 | Machine learning algorithms review Qingyang Ling · Applied and Computational Engineering | 31 May 2023 | 468 |
| 34 | A comprehensive survey on applications of transformers for deep learning tasks Saidul Islam, Hanae Elmekki, Ahmed Elsebai et al. · Expert Systems with Applications | 22 Nov 2023 | 467 |
| 35 | Basic Tenets of Classification Algorithms K-Nearest-Neighbor, Support Vector Machine, Random Forest and Neural Network: A Review Ernest Yeboah Boateng, Joseph Otoo, Daniel A. Abaye · Journal of Data Analysis and Information Processing | 2020 | 464 |
| 36 | Epileptic Seizures Detection Using Deep Learning Techniques: A Review Afshin Shoeibi, Marjane Khodatars, Navid Ghassemi et al. · International Journal of Environmental Research and Public Health | 27 May 2021 | 463 |
| 37 | Deep learning-based image recognition for autonomous driving Hironobu Fujiyoshi, Tsubasa Hirakawa, Takayoshi Yamashita · IATSS Research | Dec 2019 | 445 |
| 38 | Greek long-term energy consumption prediction using artificial neural networks Lambros Ekonomou · Energy | 8 Nov 2009 | 442 |
| 39 | A review of epileptic seizure detection using machine learning classifiers Mohammad Khubeb Siddiqui, Rubén Morales-Menéndez, Xiaodi Huang et al. · Brain Informatics | 25 May 2020 | 437 |
| 40 | Deep Industrial Image Anomaly Detection: A Survey Jiaqi Liu, Guoyang Xie, Jinbao Wang et al. · Machine Intelligence Research | 15 Jan 2024 | 416 |
| 41 | DeepDeSRT: Deep Learning for Detection and Structure Recognition of Tables in Document Images Sebastian Schreiber, Stefan Agne, Ivo Wolf et al. | Nov 2017 | 396 |
| 42 | VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization Pankaj Kumar Mishra, Riccardo Verk, Daniele Fornasier et al. · Institutional Research Information System (University of Udine) | 2021 | 393 |
| 43 | Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques Aytaç Altan, Seçkin Karasu, Stelios D. Bekiros · Chaos Solitons & Fractals | 19 Jul 2019 | 393 |
| 44 | Agricultural object detection with You Only Look Once (YOLO) Algorithm: A bibliometric and systematic literature review Chetan Badgujar, Alwin Poulose, Hao Gan · Computers and Electronics in Agriculture | 31 May 2024 | 387 |
| 45 | Blockchain Applications for Industry 4.0 and Industrial IoT: A Review Tejasvi Alladi, Vinay Chamola, Reza M. Parizi et al. · IEEE Access | 2019 | 385 |
| 46 | Blockchain solutions for big data challenges: A literature review Elena Karafiloski, Anastas Mishev | Jul 2017 | 382 |
| 47 | Fractional Neuro-Sequential ARFIMA-LSTM for Financial Market Forecasting Ayaz Hussain Bukhari, Muhammad Asif Zahoor Raja, Muhammad Sulaiman et al. · IEEE Access | 2020 | 375 |
| 48 | Fruit Image Classification Model Based on MobileNetV2 with Deep Transfer Learning Technique Yonis Gulzar · Sustainability | 19 Jan 2023 | 374 |
| 49 | Machine Learning Applications based on SVM Classification A Review Dakhaz Mustafa Abdullah, Adnan Mohsin Abdulazeez · Qubahan Academic Journal | 28 Apr 2021 | 371 |
| 50 | The Advantages and Disadvantages of the Blockchain Technology Julija Golosova, Andrejs Romānovs | Nov 2018 | 369 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.