---
title: "keras-team/keras: papers citing this GitHub repository"
description: "138 papers in the tracked journals link to the GitHub repository keras-team/keras in their Crossref records, the first in 2017; most of them (22) in 2021."
url: https://scholar4ai.com/code/github-keras-team-keras
markdown_url: https://scholar4ai.com/code/github-keras-team-keras.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "138 papers in the tracked journals link to the GitHub repository keras-team/keras in their Crossref records, the first in 2017; most of them (22) in 2021. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# keras-team/keras: papers linking to it

Research papers in the 480 tracked journals that link to keras-team/keras (https://github.com/keras-team/keras), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 64,413 stars
- 19,823 forks
- Python
- license Apache-2.0
- created 2015
- https://github.com/keras-team/keras

All repositories: https://scholar4ai.com/code.md

## Key findings

- 138 papers in the tracked journals link to the GitHub repository keras-team/keras in their Crossref records, the first in 2017; most of them (22) in 2021.
- By category: AI (113), Operations Research (15) and Marketing (2); the journals with the most are Neural Computing and Applications (37), Expert Systems with Applications (17) and Applied Intelligence (9).
- 20 of the papers build on one another: a later paper cites an earlier one that also links keras-team/keras.

## By year

*Papers linking to keras-team/keras by publication year*

| Year | Papers |
|---|---:|
| 2017 | 13 |
| 2018 | 15 |
| 2019 | 19 |
| 2020 | 22 |
| 2021 | 22 |
| 2022 | 18 |
| 2023 | 10 |
| 2024 | 11 |
| 2025 | 5 |
| 2026 | 3 |

## Journals

*Journals whose papers link to keras-team/keras most*

| Journal | Papers |
|---|---:|
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 37 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 17 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 9 |
| [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 7 |
| [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 6 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach](https://doi.org/10.1016/j.trc.2017.10.016) (Transportation Research Part C Emerging Technologies, 2017)
  - [On demand forecasting of demand-responsive paratransit services with prior reservations](https://doi.org/10.1016/j.trc.2020.102817) (Transportation Research Part C Emerging Technologies, 2020) — cites the paper above
- [Deep learning with long short-term memory networks for financial market predictions](https://doi.org/10.1016/j.ejor.2017.11.054) (European Journal of Operational Research, 2017)
  - [Forex exchange rate forecasting using deep recurrent neural networks](https://doi.org/10.1007/s42521-020-00019-x) (Digital Finance, 2020) — cites the paper above
  - [Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions](https://doi.org/10.1016/j.ejor.2020.08.001) (European Journal of Operational Research, 2020) — cites the paper above
    - [A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting](https://doi.org/10.1007/s00521-021-06548-9) (Neural Computing and Applications, 2021) — cites the paper above
  - [Stock market index prediction using transformer neural network models and frequency decomposition](https://doi.org/10.1007/s00521-024-09931-4) (Neural Computing and Applications, 2024) — cites the paper above
- [A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines](https://doi.org/10.1016/j.inffus.2017.12.007) (Information Fusion, 2017)
  - [Ruta: Implementations of neural autoencoders in R](https://doi.org/10.1016/j.knosys.2019.01.014) (Knowledge-Based Systems, 2019) — cites the paper above
- [Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation](https://doi.org/10.1016/j.eswa.2018.10.010) (Expert Systems with Applications, 2018)
  - [Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks](https://doi.org/10.1016/j.knosys.2019.104891) (Knowledge-Based Systems, 2019) — cites the paper above
- [Multi-output bus travel time prediction with convolutional LSTM neural network](https://doi.org/10.1016/j.eswa.2018.11.028) (Expert Systems with Applications, 2018)
  - [DENS-ECG: A deep learning approach for ECG signal delineation](https://doi.org/10.1016/j.eswa.2020.113911) (Expert Systems with Applications, 2020) — cites the paper above
    - [Tackling the muon identification in water Cherenkov detectors problem for the future Southern Wide-field Gamma-ray Observatory by means of machine learning](https://doi.org/10.1007/s00521-021-06730-z) (Neural Computing and Applications, 2022) — cites the paper above
- [Survey on categorical data for neural networks](https://doi.org/10.1186/s40537-020-00305-w) (Journal Of Big Data, 2020)
  - [Selecting Data Assets in Data Marketplaces](https://doi.org/10.1007/s12599-025-00940-8) (Business & Information Systems Engineering, 2025) — cites the paper above
- [Classification of olive leaf diseases using deep convolutional neural networks](https://doi.org/10.1007/s00521-020-05235-5) (Neural Computing and Applications, 2020)
  - [Image classification method on class imbalance datasets using multi-scale CNN and two-stage transfer learning](https://doi.org/10.1007/s00521-021-06066-8) (Neural Computing and Applications, 2021) — cites the paper above
- [Convolutional neural network with margin loss for fake news detection](https://doi.org/10.1016/j.ipm.2020.102418) (Information Processing & Management, 2020)
  - [DSS: A hybrid deep model for fake news detection using propagation tree and stance network](https://doi.org/10.1016/j.eswa.2022.116635) (Expert Systems with Applications, 2022) — cites the paper above

## Papers

*Papers linking to keras-team/keras, most cited first (60 of 138)*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2017-12-05 | [Deep learning with long short-term memory networks for financial market predictions](https://doi.org/10.1016/j.ejor.2017.11.054) | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | Thomas Günter Fischer, Christopher Krauß | 2,828 | cites it |
| 2017-10-24 | [Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach](https://doi.org/10.1016/j.trc.2017.10.016) | [Transportation Research Part C Emerging Technologies](https://scholar4ai.com/journals/transportation-research-part-c-emerging-technologies.md) | Jintao Ke, Hongyu Zheng, Hai Yang et al. | 728 | cites it |
| 2020-04-10 | [Survey on categorical data for neural networks](https://doi.org/10.1186/s40537-020-00305-w) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | John Hancock, Taghi M. Khoshgoftaar | 619 | cites it |
| 2017-08-31 | [Revisiting multiple instance neural networks](https://doi.org/10.1016/j.patcog.2017.08.026) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Xinggang Wang, Yongluan Yan, Peng Tang et al. | 501 | cites it |
| 2020-08-07 | [Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions](https://doi.org/10.1016/j.ejor.2020.08.001) | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | Konstantinos I. Nikolopoulos, Sushil Punia, Andreas Schäfers et al. | 499 | cites it |
| 2019-07-28 | [Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation](https://doi.org/10.1016/j.csda.2019.106816) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Yongchan Kwon, Joong‐Ho Won, Beom Joon Kim et al. | 423 | cites it |
| 2018-08-14 | [A deep learning approach for real-time detection of atrial fibrillation](https://doi.org/10.1016/j.eswa.2018.08.011) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Rasmus S. Andersen, Abdolrahman Peimankar, Sadasivan K Puthusserypady | 406 | cites it |
| 2020-11-17 | [Attention-based VGG-16 model for COVID-19 chest X-ray image classification](https://doi.org/10.1007/s10489-020-02055-x) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Chiranjibi Sitaula, Mohammad Belayet Hossain | 349 | cites it |
| 2021-05-07 | [Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset](https://doi.org/10.1007/s11263-021-01466-8) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Feifan Lv, Yu Li, Feng Lu | 324 | cites it |
| 2017-12-23 | [A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines](https://doi.org/10.1016/j.inffus.2017.12.007) | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | David Charte, Francisco Charte, Salvador García et al. | 306 | cites it |
| 2018-11-22 | [Multi-output bus travel time prediction with convolutional LSTM neural network](https://doi.org/10.1016/j.eswa.2018.11.028) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Niklas Petersen, Filipe Rodrigues, Francisco C. Pereira | 290 | cites it |
| 2021-06-21 | [Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors](https://doi.org/10.1038/s42256-021-00356-5) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Claudionor N. Coelho, Aki Kuusela, Shan Li et al. | 226 | cites it |
| 2017-10-16 | [Deep learning for freezing of gait detection in Parkinson’s disease patients in their homes using a waist-worn inertial measurement unit](https://doi.org/10.1016/j.knosys.2017.10.017) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Julià Camps, Albert Samà, Mario Martín et al. | 225 | cites it |
| 2017-09-19 | [Intraday prediction of Borsa Istanbul using convolutional neural networks and feature correlations](https://doi.org/10.1016/j.knosys.2017.09.023) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Hakan Gündüz, Yusuf Yaslan, Zehra Çataltepe | 188 | cites it |
| 2020-09-10 | [DENS-ECG: A deep learning approach for ECG signal delineation](https://doi.org/10.1016/j.eswa.2020.113911) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Abdolrahman Peimankar, Sadasivan K Puthusserypady | 175 | cites it |
| 2017-04-29 | [A hybrid recommender system using artificial neural networks](https://doi.org/10.1016/j.eswa.2017.04.046) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Tulasi K. Paradarami, Nathaniel D. Bastian, Jennifer L. Wightman | 158 | cites it |
| 2020-09-09 | [Enhancing discrete choice models with representation learning](https://doi.org/10.1016/j.trb.2020.08.006) | [Transportation Research Part B Methodological](https://scholar4ai.com/journals/transportation-research-part-b-methodological.md) | Brian Sifringer, Virginie Lurkin, Alexandre Alahi | 152 | cites it |
| 2021-10-21 | [Audio based depression detection using Convolutional Autoencoder](https://doi.org/10.1016/j.eswa.2021.116076) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Sara Sardari, Bahareh Nakisa, Mohammad Naim Rastgoo et al. | 151 | cites it |
| 2020-02-14 | [Deep-learning-based prediction of late age-related macular degeneration progression](https://doi.org/10.1038/s42256-020-0154-9) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Qi Yan, Daniel E. Weeks, Hongyi Xin et al. | 147 | cites it |
| 2021-02-26 | [BERT: a sentiment analysis odyssey](https://doi.org/10.1057/s41270-021-00109-8) | [Journal of Marketing Analytics](https://scholar4ai.com/journals/journal-of-marketing-analytics.md) | Shivaji Alaparthi, Manit Mishra | 147 | cites it |
| 2020-08-01 | [Classification of olive leaf diseases using deep convolutional neural networks](https://doi.org/10.1007/s00521-020-05235-5) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Sinan Uğuz, Nese Uysal | 144 | cites it |
| 2018-10-06 | [Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation](https://doi.org/10.1016/j.eswa.2018.10.010) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Anabel Gómez-Ríos, Siham Tabik, Julián Luengo et al. | 142 | cites it |
| 2020-10-29 | [Convolutional neural network with margin loss for fake news detection](https://doi.org/10.1016/j.ipm.2020.102418) | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | Mohammad Hadi Goldani, Reza Safabakhsh, Saeedeh Momtazi | 139 | cites it |
| 2018-08-04 | [Improved inception-residual convolutional neural network for object recognition](https://doi.org/10.1007/s00521-018-3627-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Md Zahangir Alom, Mahmudul Hasan, Chris Yakopcic et al. | 135 | cites it |
| 2020-12-25 | [CNN with depthwise separable convolutions and combined kernels for rating prediction](https://doi.org/10.1016/j.eswa.2020.114528) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Zahid Younas Khan, Zhendong Niu | 132 | cites it |
| 2022-04-21 | [Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments](https://doi.org/10.1038/s42256-022-00477-5) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Markus Marks, Jin Qiuhan, Oliver Sturman et al. | 129 | cites it |
| 2019-08-27 | [Deep learning assisted heuristic tree search for the container pre-marshalling problem](https://doi.org/10.1016/j.cor.2019.104781) | [Computers & Operations Research](https://scholar4ai.com/journals/computers-operations-research.md) | André Hottung, Shunji Tanaka, Kevin Tierney | 121 | cites it |
| 2020-05-26 | [Surrogate optimization of deep neural networks for groundwater predictions](https://doi.org/10.1007/s10898-020-00912-0) | [Journal of Global Optimization](https://scholar4ai.com/journals/journal-of-global-optimization.md) | Juliane Müller, Jangho Park, Reetik Kumar Sahu et al. | 108 | cites it |
| 2017-08-29 | [Ask Your Neurons: A Deep Learning Approach to Visual Question Answering](https://doi.org/10.1007/s11263-017-1038-2) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Mateusz Malinowski, Marcus Rohrbach, Mario Fritz | 105 | cites it |
| 2019-01-28 | [Training deep neural networks for binary communication with the Whetstone method](https://doi.org/10.1038/s42256-018-0015-y) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | William Severa, Craig Michael Vineyard, Ryan Dellana et al. | 105 | cites it |
| 2022-02-07 | [DSS: A hybrid deep model for fake news detection using propagation tree and stance network](https://doi.org/10.1016/j.eswa.2022.116635) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Mansour Davoudi, Mohammad Reza Moosavi, Mohammad Hadi Sadreddini | 94 | cites it |
| 2018-03-22 | [Pairwise based deep ranking hashing for histopathology image classification and retrieval](https://doi.org/10.1016/j.patcog.2018.03.015) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Xiaoshuang Shi, Manish Sapkota, Fuyong Xing et al. | 93 | cites it |
| 2020-03-27 | [Forex exchange rate forecasting using deep recurrent neural networks](https://doi.org/10.1007/s42521-020-00019-x) | [Digital Finance](https://scholar4ai.com/journals/digital-finance.md) | Alexander Jakob Dautel, Wolfgang Karl Härdle, Stefan Lessmann et al. | 93 | cites it |
| 2021-12-17 | [PatentNet: multi-label classification of patent documents using deep learning based language understanding](https://doi.org/10.1007/s11192-021-04179-4) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Arousha Haghighian Roudsari, Jafar Afshar, Wookey Lee et al. | 93 | cites it |
| 2019-04-17 | [DeepTrend 2.0: A light-weighted multi-scale traffic prediction model using detrending](https://doi.org/10.1016/j.trc.2019.03.022) | [Transportation Research Part C Emerging Technologies](https://scholar4ai.com/journals/transportation-research-part-c-emerging-technologies.md) | Xingyuan Dai, Rui Fu, Enmin Zhao et al. | 87 | cites it |
| 2019-11-26 | [Plus–minus player ratings for soccer](https://doi.org/10.1016/j.ejor.2019.11.026) | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | Tarak Kharrat, Ian G. McHale, Javier López Peña | 78 | cites it |
| 2020-05-19 | [T-Net: Nested encoder–decoder architecture for the main vessel segmentation in coronary angiography](https://doi.org/10.1016/j.neunet.2020.05.002) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Tae Joon Jun, Jihoon Kweon, Young‐Hak Kim et al. | 73 | cites it |
| 2023-10-05 | [A causal-temporal graphic convolutional network (CT-GCN) approach for TBM load prediction in tunnel excavation](https://doi.org/10.1016/j.eswa.2023.121977) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Xianlei Fu, Yue Pan, Limao Zhang | 68 | cites it |
| 2018-04-13 | [Vehicle classification from low-frequency GPS data with recurrent neural networks](https://doi.org/10.1016/j.trc.2018.03.024) | [Transportation Research Part C Emerging Technologies](https://scholar4ai.com/journals/transportation-research-part-c-emerging-technologies.md) | Matteo Simoncini, Leonardo Taccari, Francesco Sambo et al. | 65 | cites it |
| 2021-07-21 | [Detecting ethnicity-targeted hate speech in Russian social media texts](https://doi.org/10.1016/j.ipm.2021.102674) | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | Ekaterina Pronoza, Polina Panicheva, Olessia Y. Koltsova et al. | 65 | cites it |
| 2021-10-10 | [A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting](https://doi.org/10.1007/s00521-021-06548-9) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Hossein Abbasimehr, Reza Paki, Aram Bahrini | 65 | cites it |
| 2019-12-09 | [Predicting disease-associated mutation of metal-binding sites in proteins using a deep learning approach](https://doi.org/10.1038/s42256-019-0119-z) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Mohamad Koohi‐Moghadam, Haibo Wang, Yuchuan Wang et al. | 62 | cites it |
| 2021-04-21 | [U-net based analysis of MRI for Alzheimer’s disease diagnosis](https://doi.org/10.1007/s00521-021-05983-y) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Zhonghao Fan, Johann Li, Liang Zhang et al. | 61 | cites it |
| 2022-08-29 | [Machine learning-based proactive social-sensor service for mental health monitoring using twitter data](https://doi.org/10.1016/j.jjimei.2022.100113) | [International Journal of Information Management Data Insights](https://scholar4ai.com/journals/international-journal-of-information-management-data-insights.md) | Shailesh Hinduja, Mahbuba Afrin, Sajib Mistry et al. | 61 | cites it |
| 2023-09-25 | [Improving flight delays prediction by developing attention-based bidirectional LSTM network](https://doi.org/10.1016/j.eswa.2023.121747) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Maged Mamdouh, Mostafa Ezzat, Hesham Ahmed Hefny | 61 | cites it |
| 2017-05-31 | [Lexicon-free fingerspelling recognition from video: Data, models, and signer adaptation](https://doi.org/10.1016/j.csl.2017.05.009) | [Computer Speech & Language](https://scholar4ai.com/journals/computer-speech-language.md) | Tae-Hwan Kim, Jonathan Keane, Weiran Wang et al. | 59 | cites it |
| 2018-07-21 | [Deep learning to detect botnet via network flow summaries](https://doi.org/10.1007/s00521-018-3595-x) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Abdurrahman Pektaş, Tankut Acarman | 57 | cites it |
| 2017-07-29 | [On the effects of using word2vec representations in neural networks for dialogue act recognition](https://doi.org/10.1016/j.csl.2017.07.009) | [Computer Speech & Language](https://scholar4ai.com/journals/computer-speech-language.md) | Christophe Cerisara, Pavel Král, Ladislav Lenc | 53 | cites it |
| 2019-07-29 | [Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks](https://doi.org/10.1016/j.knosys.2019.104891) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Anabel Gómez-Ríos, Siham Tabik, Julián Luengo et al. | 52 | cites it |
| 2021-07-07 | [Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation](https://doi.org/10.1007/s10994-021-06006-6) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Srivatsan Krishnan, Behzad Boroujerdian, William Fu et al. | 50 | cites it |
| 2020-09-18 | [Semi-supervised deep learning based named entity recognition model to parse education section of resumes](https://doi.org/10.1007/s00521-020-05351-2) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Bodhvi Gaur, Gurpreet Singh Saluja, Hamsa Bharathi Sivakumar et al. | 49 | cites it |
| 2023-05-05 | [Siamese neural networks in recommendation](https://doi.org/10.1007/s00521-023-08610-0) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Nicolás Serrano, Alejandro Bellogín | 49 | cites it |
| 2021-02-27 | [The automatic detection of heart failure using speech signals](https://doi.org/10.1016/j.csl.2021.101205) | [Computer Speech & Language](https://scholar4ai.com/journals/computer-speech-language.md) | Mittapalle Kiran Reddy, Pyry Helkkula, Y. Madhu Keerthana et al. | 47 | cites it |
| 2020-07-01 | [Supervised feature selection through Deep Neural Networks with pairwise connected structure](https://doi.org/10.1016/j.knosys.2020.106202) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Yingkun Huang, Weidong Jin, Zhibin Yu et al. | 45 | cites it |
| 2022-10-07 | [Deep learning models for vessel’s ETA prediction: bulk ports perspective](https://doi.org/10.1007/s10696-022-09471-w) | [Flexible Services and Manufacturing Journal](https://scholar4ai.com/journals/flexible-services-and-manufacturing-journal.md) | Sara El Mekkaoui, Loubna Benabbou, Abdelaziz Berrado | 43 | cites it |
| 2023-03-10 | [Deep Learning in Employee Selection: Evaluation of Algorithms to Automate the Scoring of Open-Ended Assessments](https://doi.org/10.1007/s10869-023-09874-y) | [Journal of Business and Psychology](https://scholar4ai.com/journals/journal-of-business-and-psychology.md) | Isaac Benjamin Thompson, Nick Koenig, Derek L. Mracek et al. | 42 | cites it |
| 2021-05-25 | [TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes](https://doi.org/10.1016/j.eswa.2021.115211) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Tae Joon Jun, Youngsub Eom, Do‐Hyeun Kim et al. | 41 | cites it |
| 2021-09-06 | [Unsupervised feature learning-based encoder and adversarial networks](https://doi.org/10.1186/s40537-021-00508-9) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Endang Suryawati, Hilman  Ferdinandus Pardede, Vicky Zilvan et al. | 41 | cites it |
| 2019-09-05 | [Fine-grained action segmentation using the semi-supervised action GAN](https://doi.org/10.1016/j.patcog.2019.107039) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Harshala Gammulle, Simon Denman, Sridha Sridharan et al. | 40 | cites it |
| 2021-05-28 | [Deep neural network compression through interpretability-based filter pruning](https://doi.org/10.1016/j.patcog.2021.108056) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Kaixuan Yao, Feilong Cao, Yee Leung et al. | 40 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). keras-team/keras: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-keras-team-keras

```bibtex
@misc{scholar4ai-code-github-keras-team-keras,
  author = {{Scholar4AI}},
  title = {keras-team/keras: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-keras-team-keras}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).