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Showing 19 of 39 academic articles

Multi‐object tracking using dominant sets

Yonatan T. Tesfaye, Eyasu Zemene, Marcello Pelillo, Andrea Prati • IET Computer Vision (2016)

Multi‐object tracking is an interesting but challenging task in the field of computer vision. Most previous works based on data association techniques merely take into account the relationship between detection responses in a locally limite...

DOAJ Open Access (DOAJ) DOI: 10.1049/iet-cvi.2015.0297

MaskDis R‐CNN: An instance segmentation algorithm with adversarial network for herd pigs

Shuqin Tu, Qiantao Zeng, Haofeng Liu, Yun Liang et al. • IET Image Processing (2023)

Abstract The current instance segmentation method can achieve satisfactory results in common scenarios. However, under the overlap or partial occlusion between targets caused by the complex scenes, accurate segmentation of pigs remains a ch...

DOAJ Open Access (DOAJ) DOI: 10.1049/ipr2.12880

Experimental study of a novel contact-based pose detection approach for digital twin-driven high-precision micro assembly

Nazeer Bilal, Pradeep Carol Santhosh, Vargas Patricia A., Erden Mustafa Suphi et al. • Manufacturing Review (2025)

This study presents a comprehensive study of a novel Contact-Based Pose Estimation Method (CBPEM) for enhancing precision in robotic assembly processes within digital twin frameworks. Conventional pose detection methods, such as laser and c...

DOAJ Open Access (DOAJ) DOI: 10.1051/mfreview/2025004

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose estimation

Jhansi Rani Challapalli, Nagaraju Devarakonda • Machine Learning: Science and Technology (2023)

Multi-person pose estimation (MPE) remains a significant and intricate issue in computer vision. This is considered the human skeleton joint identification issue and resolved by the joint heat map regression network lately. Learning robust ...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/acc9fc

A lightweight optimization framework for real-time pedestrian detection in dense and occluded scenes

C. Chen, J. Li, J. Li, Z. Shuai et al. • Mechanical Sciences (2025)

Pedestrian detection is one of the most widely applied tasks in industrial computer vision. It encapsulates three core challenges of object detection: detecting small objects, handling heavy occlusion, and balancing speed and accuracy for d...

DOAJ Open Access (DOAJ) DOI: 10.5194/ms-16-877-2025

Ear biometrics in computer vision

Mark J. Burge, Wilhelm Burger • Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition (2002)

A class of biometrics based upon ear features is introduced for use in the development of passive identification systems. The viability of the proposed biometric is shown both theoretically in terms of the uniqueness and measurability over ...

OPENALEX DOI: https://doi.org/10.1109/icpr.2000.906202

Emerging Trends in Autonomous Vehicle Perception: Multimodal Fusion for 3D Object Detection

Simegnew Yihunie Alaba, Ali C. Gurbuz, John E. Ball • World Electric Vehicle Journal (2024)

The pursuit of autonomous driving relies on developing perception systems capable of making accurate, robust, and rapid decisions to interpret the driving environment effectively. Object detection is crucial for understanding the environmen...

DOAJ Open Access (DOAJ) DOI: 10.3390/wevj15010020

Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks

Marco Antonio Contreras-Cruz, Juan Pablo Ramirez-Paredes, Uriel Haile Hernandez-Belmonte, Victor Ayala-Ramirez • Sensors (2019)

One of the essential abilities in animals is to detect novelties within their environment. From the computational point of view, novelty detection consists of finding data that are different in some aspect to the known data. In robotics, re...

DOAJ Open Access (DOAJ) DOI: 10.3390/s19132965

A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence

Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar et al. • Technologies (2023)

Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies11020055

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

PharmaNet Deep: Real-Time Pharmaceutical Defect Detection Using Defect-Guided Feature Fusion and Uncertainty-Driven Inspection

Ajantha Vijayakumar, Joseph Abraham Sundar Koilraj, Muthaiah Rajappa • International Journal of Computational Intelligence Systems (2025)

Abstract Oral dosage forms are the most widely employed method of drug delivery in therapeutic treatments. However, the presence of visual defects in blister packages can adversely affect the drug's bioavailability and therapeutic efficacy,...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-025-00986-2

Exploiting the features of deep residual network with SVM classifier for human posture recognition.

Irfan Kareem, Syed Farooq Ali, Muhammad Bilal, Muhammad Shehzad Hanif • PLoS ONE (2024)

Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in th...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0314959

A hybrid transformer–neuromorphic framework for robust pest detection in agriculture

Subhranil Das, Rashmi Kumari, Raghwendra Kishore Singh, Tanupriya Choudhury • Discover Artificial Intelligence (2026)

Abstract Detecting pests in agricultural fields remains one of the challenging tasks due to the small size of the objects and occlusion effects. In this paper, Trans-Neu-Pest, a hybrid framework, has been proposed by integrating the Swin Tr...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-01824-w

Artificial Intelligence and Acute Stroke Imaging

J.E. Soun, D.S. Chow, M. Nagamine, R.S. Takhtawala et al. • American Journal of Neuroradiology (2020)

Artificial intelligence technology is a rapidly expanding field with many applications in acute stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute stroke is critical for initiating prompt intervention ...

OPENALEX cc-by DOI: https://doi.org/10.3174/ajnr.a6883 PMC: 7814792