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Multi-scale attention and collaborative fusion for enhanced RGB-D salient object detection in weld quality inspection

Zhiwen Xiong, Yuanchun Li • Scientific Reports (2026)

Abstract Salient object detection (SOD) plays a crucial role in computer vision by mimicking human visual attention to identify and segment the most prominent objects in a scene. The advent of depth sensing technologies has propelled RGB-D ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-56237-7

Computer vision and machine‐learning techniques for quantification and predictive modeling of intracellular anticancer drug delivery by nanocarriers

Sanjay Goswami, Kshama D. Dhobale, Ravindra D. Wavhale, Barnali Goswami et al. • Applied AI Letters (2022)

Abstract The field of cancer nanomedicine has made significant progress, but its clinical translation is impeded by many challenges, such as the difficulty in analyzing intracellular anticancer drug release by the nanocarriers due to the la...

DOAJ Open Access (DOAJ) DOI: 10.1002/ail2.50

Euclid Quick Data Release (Q1)

Bazzanini L., Angora G., Bergamini P., Meneghetti M. et al. • Astronomy & Astrophysics (2026)

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust a...

DOAJ Open Access (DOAJ) DOI: 10.1051/0004-6361/202557590

Computer vision technology in agricultural automation —A review

Hongkun Tian, Tianhai Wang, Yadong Liu, Xi Qiao et al. • Information Processing in Agriculture (2019)

Computer vision is a field that involves making a machine “see”. This technology uses a camera and computer instead of the human eye to identify, track and measure targets for further image processing. With the development of computer visio...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.inpa.2019.09.006

A review of convolutional neural networks in computer vision

Xia Zhao, Limin Wang, Yufei Zhang, Xuming Han et al. • Artificial Intelligence Review (2024)

Abstract In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of dee...

OPENALEX cc-by DOI: https://doi.org/10.1007/s10462-024-10721-6

Enhancing image caption generation through context-aware attention mechanism

Ahatesham Bhuiyan, Eftekhar Hossain, Mohammed Moshiul Hoque, M. Ali Akber Dewan • Heliyon (2024)

Image captioning, the process of generating natural language descriptions based on image content, has garnered attention in AI research for its implications in scene understanding and human-computer interaction. While much prior research ha...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2024.e36272

Addressing practical challenge of using autopilot drone for asphalt surface monitoring: Road detection, segmentation, and following

Hormazd Ranjbar, Perry Forsythe, Alireza Ahmadian Fard Fini, Mojtaba Maghrebi et al. • Results in Engineering (2023)

According to the recent world bank report, around 80% of a life-cycle cost of a road is devoted to maintenance which includes monitoring and repair processes. To more effectively keep road serviceability, knowing the current status of road ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.rineng.2023.101130

Computer Vision for Autonomous Vehicles

Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger • Foundations and Trends® in Computer Graphics and Vision (2020)

Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the fiel...

OPENALEX Open Access DOI: https://doi.org/10.1561/0600000079

Architectural Framework to Enhance Image-Based Vehicle Positioning for Advanced Functionalities

Iosif-Alin Beti, Paul-Corneliu Herghelegiu, Constantin-Florin Caruntu • Information (2024)

The growing number of vehicles on the roads has resulted in several challenges, including increased accident rates, fuel consumption, pollution, travel time, and driving stress. However, recent advancements in intelligent vehicle technologi...

DOAJ Open Access (DOAJ) DOI: 10.3390/info15060323

CG-DINO: Improved Network for Small Object Detection in Uncrewed Aerial Vehicle Imagery Based on DINO

Jian Liu, Pei Niu, Yihui Jiang, Zilong Zhao et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2026)

Object detection in uncrewed aerial vehicle (UAV) acquired images remains a challenging task due to extreme scale variation, dense object layouts, and complex backgrounds, etc. Although convolutional neural networks (CNNs), transformers, an...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2026.3729713

Artificial neural networks

J. J. Hopfield • IEEE Circuits and Devices Magazine (1988)

Examines the following questions associated with artificial neural networks: why people are interested in artificial neural networks; what artificial neural networks are, from the point of view of electronic circuits, and how they work; how...

OPENALEX DOI: https://doi.org/10.1109/101.8118

Deep Learning in Image Cytometry: A Review

Anindya Gupta, Philip John Harrison, Håkan Wieslander, Nicolas Pielawski et al. • Cytometry Part A (2018)

Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and ho...

OPENALEX cc-by-nc DOI: https://doi.org/10.1002/cyto.a.23701 PMC: 6590257

Deep Learning for Time Series Anomaly Detection: A Survey

Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charų C. Aggarwal et al. • ACM Computing Surveys (2024)

Time series anomaly detection is important for a wide range of research fields and applications, including financial markets, economics, earth sciences, manufacturing, and healthcare. The presence of anomalies can indicate novel or unexpect...

OPENALEX cc-by DOI: https://doi.org/10.1145/3691338

Deep learning for digital holography: a review

Tianjiao Zeng, Yanmin Zhu, Edmund Y. M. Lam • Optics Express (2021)

Recent years have witnessed the unprecedented progress of deep learning applications in digital holography (DH). Nevertheless, there remain huge potentials in how deep learning can further improve performance and enable new functionalities ...

OPENALEX Open Access DOI: https://doi.org/10.1364/oe.443367

A Review of Deep Learning Applications in Intrusion Detection Systems: Overcoming Challenges in Spatiotemporal Feature Extraction and Data Imbalance

Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences (2025)

In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15031552

A Comprehensive Survey on Graph Anomaly Detection With Deep Learning

Xiaoxiao Ma, Jia Xin Wu, Shan Xue, Jian Yu Yang et al. • IEEE Transactions on Knowledge and Data Engineering (2021)

Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...

OPENALEX Open Access DOI: https://doi.org/10.1109/tkde.2021.3118815