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Showing 17 of 37 academic articles

A Methodological Review on Prediction of Multi-Stage Hypovigilance Detection Systems Using Multimodal Features

Qaisar Abbas, Abdullah Alsheddy • IEEE Access (2021)

Several hypovigilance detection systems (HDx) were developed to avoid road-side accidents due to driver fatigue. They have suffered from several limitations. Notably many of these are focused on center-head position to define an area of int...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3068343

The NWRD Dataset: An Open-Source Annotated Segmentation Dataset of Diseased Wheat Crop

Hirra Anwar, Saad Ullah Khan, Muhammad Mohsin Ghaffar, Muhammad Fayyaz et al. • Sensors (2023)

Wheat stripe rust disease (WRD) is extremely detrimental to wheat crop health, and it severely affects the crop yield, increasing the risk of food insecurity. Manual inspection by trained personnel is carried out to inspect the disease spre...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23156942

Automated Cell Foreground–Background Segmentation with Phase-Contrast Microscopy Images: An Alternative to Machine Learning Segmentation Methods with Small-Scale Data

Guochang Ye, Mehmet Kaya • Bioengineering (2022)

Cell segmentation is a critical step for image-based experimental analysis. Existing cell segmentation methods are neither entirely automated nor perform well under basic laboratory microscopy. This study proposes an efficient and automated...

DOAJ Open Access (DOAJ) DOI: 10.3390/bioengineering9020081

A Framework for Instantaneous Driver Drowsiness Detection Based on Improved HOG Features and Naïve Bayesian Classification

Samy Bakheet, Ayoub Al-Hamadi • Brain Sciences (2021)

Due to their high distinctiveness, robustness to illumination and simple computation, Histogram of Oriented Gradient (HOG) features have attracted much attention and achieved remarkable success in many computer vision tasks. In this paper, ...

DOAJ Open Access (DOAJ) DOI: 10.3390/brainsci11020240

Edge-intelligent lightweight vision system for perspective-corrected egg-cage matching in cage-reared ducks

Dakang Guo, Jiatao Wang, Zeyuan Lin, Youfu Liu et al. • Poultry Science (2026)

In the stereoscopic cage-rearing system, monitoring the individual egg production of laying ducks is essential for identifying low-yield individuals and optimizing breeding management. To overcome the high deployment cost of multi-sensor mo...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.psj.2026.106479

Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution

Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG et al. • Meitan kexue jishu (2024)

The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by under...

DOAJ Open Access (DOAJ) DOI: 10.12438/cst.2023-1597

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

Evaluating the ergonomic deficiencies in computer workstations and investigating their correlation with reported musculoskeletal disorders and visual symptoms among computer users in Bangladeshi university

Md Golam Kibria, Md Shohel Parvez, Palash Saha, Subrata Talapatra • Heliyon (2023)

Background: Nowadays, computer users are facing musculoskeletal disorders (MSDs) and visual symptoms. Prolonged sitting in inappropriate, awkward, and static postures on the computer workstation may cause musculoskeletal disorders (MSDs). S...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2023.e22179

Face recognition with Bayesian convolutional networks for robust surveillance systems

Umara Zafar, Mubeen Ghafoor, Tehseen Zia, Ghufran Ahmed et al. • EURASIP Journal on Image and Video Processing (2019)

Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13640-019-0406-y

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

An integrated method for color correction based on color constancy for early mural images in Mogao Grottoes

Zhen Liu, Zhen Liu, Yi-Xuan Liu, Gui-Ai Gao et al. • Frontiers in Neuroscience (2022)

Restoring the correct or realistic color of a cultural heritage object is a crucial problem for imaging techniques. Digital images often have undesired color casts due to adverse effects caused by unstable illuminant conditions, vignetting,...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnins.2022.1024599

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Nodir Rakhimov, Jura Kuvandikov, Ma'ruf Tojiyev, Dilmurod Khasanov et al. • Frontiers in Artificial Intelligence (2026)

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1910842