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Text Data Augmentation for Deep Learning

Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht • Journal Of Big Data (2021)

Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augme...

OPENALEX cc-by DOI: https://doi.org/10.1186/s40537-021-00492-0 PMC: 8287113

Object Detection With Deep Learning: A Review

Zhong‐Qiu Zhao, Peng Zheng, Shou-Tao Xu, Xindong Wu • IEEE Transactions on Neural Networks and Learning Systems (2019)

Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2018.2876865

A Fast Inference Vision Transformer for Automatic Pavement Image Classification and Its Visual Interpretation Method

Yihan Chen, Xingyu Gu, Zhen Liu, Jia Liang • Remote Sensing (2022)

Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful a...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14081877

Deep learning and education for sustainability

Kevin Warburton • International Journal of Sustainability in Higher Education (2003)

Deep learning is a key strategy by which students extract meaning and understanding from course materials and experiences. Because of the range and interconnectedness of environmental, social and economic issues, and the importance of inter...

OPENALEX DOI: https://doi.org/10.1108/14676370310455332

Deep Learning Based Recommender System

Shuai Zhang, Lina Yao, Aixin Sun, Yi Tay • ACM Computing Surveys (2019)

With the growing volume of online information, recommender systems have been an effective strategy to overcome information overload. The utility of recommender systems cannot be overstated, given their widespread adoption in many web applic...

OPENALEX Open Access DOI: https://doi.org/10.1145/3285029

Precise Cruise Control for Fixed-Wing Aircraft Based on Proximal Policy Optimization with Nonlinear Attitude Constraints

Haotian Wu, Yan Guo, Juliang Cao, Zhiming Xiong et al. • Aerospace (2025)

In response to the issues of severe pitch oscillation and unstable roll attitude present in existing reinforcement learning-based aircraft cruise control methods during dynamic maneuvers, this paper proposes a precise control method for air...

DOAJ Open Access (DOAJ) DOI: 10.3390/aerospace12080670

Does Emotional Labor Matter for University Teaching? Examining the Antecedents and Consequences of University Teachers' Emotional Labor Strategies

Jiying Han, Hongbiao Yin, Xin Yang, Feifei Wang • Frontiers in Psychology (2021)

Following Grandey's integrative model of emotional labor and emotion regulation, this study examined the relationships between university teachers' reported use of various emotional labor strategies and some antecedents (i. e., perceived em...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyg.2021.731099

Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance

Chirag Gupta, Venkategowda Ramegowda, Supratim Basu, Andy Pereira • Frontiers in Genetics (2021)

Gene regulatory networks underpin stress response pathways in plants. However, parsing these networks to prioritize key genes underlying a particular trait is challenging. Here, we have built the Gene Regulation and Association Network (GRA...

DOAJ Open Access (DOAJ) DOI: 10.3389/fgene.2021.652189

Performance Analysis and Optimization of Terahertz Metamaterial Absorbers Using Machine Learning-Based Inverse Modeling

Oishi Jyoti, Md. Samiul Habib, Nguyen Hoang Hai, S. M. Abdur Razzak • IEEE Access (2025)

We present a tunable broadband terahertz (THz) metamaterial absorber with a structurally simple, single-layered vanadium dioxide (VO2) elliptical ring resonator. This design achieves a wide, near-perfect absorption band (3.5–5 THz) w...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3631711

A synergistic enhancement of the Ivy algorithm for GAN-based imbalanced classification

Hanjie Xu, Jian Xiong, Jinyu Wu, Xianlai Zhou et al. • Scientific Reports (2025)

Abstract The Ivy Algorithm (IVYA), a swarm intelligence algorithm inspired by plant growth, presents a novel framework for optimization. To unlock its full potential in complex, high-dimensional problems, it is crucial to address the fundam...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-32510-z

High temperature Nb-Si alloys using data science: optimization of fracture toughness and high-temperature strength

Chao Xu, Dezhi Chen, Xiaofu Zhang, Qi Wang et al. • Nature Communications (2026)

Abstract High temperature Nb-Si based alloys face a critical challenge: achieving adequate room-temperature fracture toughness ( > 18 MPa·m1/2) for processing while maintaining high-temperature strength, properties that typically compete wi...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41467-026-75353-6

An introduction to quantum machine learning

Maria Schuld, Ilya Sinayskiy, Francesco Petruccione • Contemporary Physics (2014)

Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition or strategy optimisation, with growing applications in the IT...

OPENALEX Open Access DOI: https://doi.org/10.1080/00107514.2014.964942

Development of a Transfer Learning Technique for Rapid Adaptation of Thermal Compensation Models to Long-Term Machine Thermal Behavior Changes

Chia-Chin Chuang, Zheng-Wei Lin Chi, Tzu-Chien Kuo, Che-Jui Chang et al. • Machines (2026)

Structural aging and environmental changes associated with long-term operation can substantially modify the thermal behavior of machine tools, diminishing the accuracy of existing thermal compensation models. Traditional neural network appr...

DOAJ Open Access (DOAJ) DOI: 10.3390/machines14030309

Evaluation of Predictive Maintenance by Marginal Utility: A Case Study on Offshore Wind

Rasmus Dovnborg Frederiksen, Grzegorz Radzki, Grzegorz Bocewicz, Peter Nielsen et al. • Applied Sciences (2026)

This paper investigates the relationship between the benefits achieved by predictive maintenance implementation and the related costs incurred intentionally or not. Specifically, we seek to establish an evaluation method for predictive main...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16178708

Information disclosure and funding success of green crowdfunding campaigns: a study on GoFundMe

Ziyi Yin, Guowei Huang, Rui Zhao, Sen Wang et al. • Financial Innovation (2024)

Abstract Crowdfunding has become important in increasing financial support for the development of green technologies. Self-disclosed information significantly affects supporters’ decisions and is important for the success of green project f...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40854-024-00666-8

Hyperparameter Search in Machine Learning

Marc Claesen, Bart De Moor • arXiv (Cornell University) (2015)

We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt to build models that capture some element of interest based o...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1502.02127

A Protein‐Centric Strategy Coupled with Match‐Between‐Run Glycoproteomics Enables Discovery of Robust Site‐Specific Glycan Biomarkers for Hepatocellular Carcinoma

Lei Liu, Taiheng Ma, Qi Liu, He Zhu et al. • Advanced Science (2026)

ABSTRACT Dysregulated protein glycosylation is a hallmark of cancer, and systematic investigation of glycosylation patterns is crucial for identifying biomarkers. However, current glycoproteomic studies are constrained by the limited quanti...

DOAJ Open Access (DOAJ) DOI: 10.1002/advs.202516299

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Mafalda Reis Pereira, Mafalda Reis Pereira, Filipe Neves dos Santos, Fernando Tavares et al. • Frontiers in Plant Science (2023)

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpls.2023.1242201