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An optimized deep learning framework for temporally stable real-time face detection in unconstrained video streams

P. E. Janani Pappu, B. Devanthan • Discover Artificial Intelligence (2026)

Abstract Face detection in real-time video streams remains challenging because of dynamic variations in illumination, pose, motion blur, and partial occlusion. This paper proposes an optimized deep learning framework that integrates YOLOv12...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-02275-z

Deep Learning for Portfolio Optimization

Zihao Zhang, Stefan Zohren, Stephen Roberts • The Journal of Financial Data Science (2020)

In this article, the authors adopt deep learning models to directly optimize the portfolio Sharpe ratio. The framework they present circumvents the requirements for forecasting expected returns and allows them to directly optimize portfolio...

OPENALEX Open Access DOI: https://doi.org/10.3905/jfds.2020.1.042

Improved sports image classification using deep neural network and novel tuna swarm optimization

Zetian Zhou, Heqing Zhang, Mehdi Effatparvar • Scientific Reports (2024)

Abstract Sports image classification is a complex undertaking that necessitates the utilization of precise and robust techniques to differentiate between various sports activities. This study introduces a novel approach that combines the de...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-024-64826-7

Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization

Junjie Ji, Yongzhang Zhou, Qiuming Cheng, Shoujun Jiang et al. • Land (2023)

Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative ...

DOAJ Open Access (DOAJ) DOI: 10.3390/land12061125

Comprehensive framework of machine learning and deep learning architectures with metaheuristic optimization for high-fidelity prediction of nanofluid specific heat capacity

Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports (2025)

Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-28268-z

Automated deep bottleneck residual 82-layered architecture with Bayesian optimization for the classification of brain and common maternal fetal ultrasound planes

Fatima Rauf, Muhammad Attique Khan, Ali Kashif Bashir, Kiran Jabeen et al. • Frontiers in Medicine (2023)

Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2023.1330218

The unreasonable effectiveness of deep learning in artificial intelligence

Terrence J. Sejnowski A B • Proceedings of the National Academy of Sciences (2020)

Deep learning networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks to real-world problems have become ubiqui...

OPENALEX Open Access DOI: https://doi.org/10.1073/pnas.1907373117 PMC: 7720171

A Survey on Deep Learning for Software Engineering

Yanming Yang, Xin Xia, David Lo, John Grundy • ACM Computing Surveys (2021)

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstr...

OPENALEX Open Access DOI: https://doi.org/10.1145/3505243

Vison transformer adapter-based hyperbolic embeddings for multi-lesion segmentation in diabetic retinopathy

Zijian Wang, Haimei Lu, Haixin Yan, Hongxing Kan et al. • Scientific Reports (2023)

Abstract Diabetic Retinopathy (DR) is a major cause of blindness worldwide. Early detection and treatment are crucial to prevent vision loss, making accurate and timely diagnosis critical. Deep learning technology has shown promise in the a...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-023-38320-5

Spatiotemporal prediction of sneeze pollutants in enclosed spaces: a CNN-LSTM approach validated by field measurements and CFD-Robotics arm twin system

Mingyu Zhao, Shujia Zhang, Ke Li, Yanru Zhang et al. • Frontiers in Robotics and AI (2026)

Densely populated enclosed environments, characterized by complex thermal stratification and overlapping breathing zones, represent high-risk clusters for the airborne transmission of respiratory pathogens. To address the dual challenges of...

DOAJ Open Access (DOAJ) DOI: 10.3389/frobt.2026.1846010

ACtriplet: An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training

Xinxin Yu, Yimeng Wang, Long Chen, Weihua Li et al. • Journal of Pharmaceutical Analysis (2025)

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid m...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jpha.2025.101317

Deep learning: a statistical viewpoint

Peter L. Bartlett, Andrea Montanari A, Alexander Rakhlin • Acta Numerica (2021)

The remarkable practical success of deep learning has revealed some major surprises from a theoretical perspective. In particular, simple gradient methods easily find near-optimal solutions to non-convex optimization problems, and despite g...

OPENALEX cc-by DOI: https://doi.org/10.1017/s0962492921000027

Distributed biconnectivity-preserving flocking with fast obstacle avoidance for UAV swarms

Jiaxin Li, Tong Duan, Peng Yi, Zhen Zhang et al. • Complex & Intelligent Systems (2026)

Abstract Obstacles in low-altitude environments force unmanned aerial vehicle (UAV) swarms to frequently alter their flight paths and communication links, which can easily cause network interruptions. It remains a significant challenge for ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s40747-026-02343-y

Rider Optimization With Deep Learning Based Image Encryption for Secure Drone Communication

N. Kannaiya Raja, E. Laxmi Lydia, Thumpala Archana Acharya, K. Radhika et al. • IEEE Access (2023)

In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3324068

A novel agricultural commodity price prediction model integrating deep learning and enhanced swarm intelligence algorithm.

Kaixuan Sun, Qi Yao, Yanhui Li • PLoS ONE (2025)

The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challengi...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0337103