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Adversarial Attack on Object Detection via Object Feature-Wise Attention and Perturbation Extraction

Wei Xue, Xiaoyan Xia, Pengcheng Wan, Ping Zhong et al. • Tsinghua Science and Technology (2025)

Deep neural networks are commonly used in computer vision tasks, but they are vulnerable to adversarial samples, resulting in poor recognition accuracy. Although traditional algorithms that craft adversarial samples have been effective in a...

DOAJ Open Access (DOAJ) DOI: 10.26599/TST.2024.9010029

Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration

Francisco Troncoso-Pastoriza, Javier López-Gómez, Lara Febrero-Garrido • Sensors (2018)

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporati...

DOAJ Open Access (DOAJ) DOI: 10.3390/s18072364

Quaternions in Computer Vision and Robotics

Edward Pervin, Jon A. Webb • Defense Technical Information Center (DTIC) (1982)

Computer vision and robotics suffer from not having good tools for manipulating three-dimensional objects. Vectors, coordinate geometry, and trigonometry all have deficiencies. Quaternions can be used to solve many of these problems. Many p...

OPENALEX DOI: https://doi.org/10.21236/ada125076

A Space-Time Partial Differential Equation Based Physics-Guided Neural Network for Sea Surface Temperature Prediction

Taikang Yuan, Junxing Zhu, Wuxin Wang, Jingze Lu et al. • Remote Sensing (2023)

Sea surface temperature (SST) prediction has attracted increasing attention, due to its crucial role in understanding the Earth’s climate and ocean system. Existing SST prediction methods are typically based on either physics-based numerica...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs15143498

Deep learning in omics: a survey and guideline

Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics (2018)

Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...

OPENALEX DOI: https://doi.org/10.1093/bfgp/ely030

Applications of Shaped-Charge Learning

Boris Galitsky • Entropy (2023)

It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy ...

DOAJ Open Access (DOAJ) DOI: 10.3390/e25111496

Deep Learning for Generic Object Detection: A Survey

Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth et al. • International Journal of Computer Vision (2019)

Abstract Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural images. Deep learning techniques have emerged as a ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11263-019-01247-4

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning SystemResearch in context

Ruichen Rong, Yonglong Wei, Lin Li, Tao Wang et al. • EBioMedicine (2023)

Summary: Background: Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ebiom.2023.104698

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

Stealing Hyperparameters in Machine Learning

Binghui Wang, Neil Zhenqiang Gong • IEEE Symposium on Security and Privacy (S&P) (2018)

Hyperparameters are critical in machine learning, as different hyperparameters often result in models with significantly different performance. Hyperparameters may be deemed confidential because of their commercial value and the confidentia...

OPENALEX Open Access DOI: https://doi.org/10.1109/sp.2018.00038

Real time identification of phishing attacks through machine learning enhanced browser extensions

Monika Dandotiya, Nikhil Kumar Goyal, Ajay Khunteta, Babita Tiwari • Scientific Reports (2026)

Abstract Phishing attack continues to rank among the deadliest online threats. They create phony websites in an attempt to obtain personal data. This study offers a framework for a browser extension that uses machine learning to examine URL...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-35655-7