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Academic Articles & Research Papers
Showing 20 of 748 academic articles
Xiufeng Wu, Xueli Li, Guangxing Cao, Chao Guo et al. • IEEE Access
(2024)
Bolts are critical components of tunnel linings, essential for ensuring safe tunnel operation. Due to their susceptibility to corrosion and detachment, it is vital to closely monitor them during maintenance. However, identifying a large num...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3513697
Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin et al. • Visual Intelligence
(2024)
Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...
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Open Access (DOAJ)
DOI: 10.1007/s44267-024-00070-x
Lijie Geng, Pengji Yan, Zhikun Ji, Chunyu Song et al. • Journal of Cotton Research
(2024)
Abstract Background The lint percentage of seed cotton is one of the most important parameters for evaluating seed cotton quality and affects its price. The traditional measuring method of lint percentage is labor-intensive and time-consumi...
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Open Access (DOAJ)
DOI: 10.1186/s42397-024-00178-x
Direselign Addis Tadesse, Chuan-Ming Liu, Van-Dai Ta • Applied Sciences
(2020)
Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the freque...
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Open Access (DOAJ)
DOI: 10.3390/app10134474
Yuan Zi, Chenyu Zhou, Jiefu Chen, Zhu Han et al. • IEEE Access
(2025)
Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earthȁ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3597991
Joanna ŁABĘDZKA • Problemy Eksploatacji
(2016)
The traditional approach to forecasting lies in the assumption that, byapplying a set of powerful analytic tools, the future could be predictedaccurately enough to choose an appropriate strategic direction for it. Theprocess often involves ...
DOAJ
Open Access (DOAJ)
DOI: 10.5604/01.3001.0055.6305
Saleh Albahli, Nudrat Nida, Aun Irtaza, Muhammad Haroon Yousaf et al. • IEEE Access
(2020)
Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3035345
Rittik Chandra Das Turjy, Fahmid Al Farid, Fahmid Al Farid, Md. Hasan Imam Bijoy et al. • Frontiers in Artificial Intelligence
(2026)
Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/frai.2026.1884567
Wenlin Yan, Xianxin Jiang, Ping Liu • IEEE Access
(2023)
Artificial Intelligence (AI) has promising applications in basketball shooting analysis, as it can help basketball athletes improve their shooting techniques and accuracy, thereby enhancing the effectiveness of both games and training sessi...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3304631
Muhammad Salihin Saealal, Mohd Zamri Ibrahim, David. J. Mulvaney, Mohd Ibrahim Shapiai et al. • PLoS ONE
(2022)
Deep learning is notably successful in data analysis, computer vision, and human control. Nevertheless, this approach has inevitably allowed the development of DeepFake video sequences and images that could be altered so that the changes ar...
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Open Access (DOAJ)
Yinsheng Zhang, Xudong Yang, Yongbo Cheng, Xiaojun Wu et al. • Current Research in Food Science
(2024)
Background: Fruit freshness detection by computer vision is essential for many agricultural applications, e.g., automatic harvesting and supply chain monitoring. This paper proposes to use the multi-task learning (MTL) paradigm to build a d...
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Open Access (DOAJ)
DOI: 10.1016/j.crfs.2024.100733
Donald Shenaj, Giulia Rizzoli, Pietro Zanuttigh • IEEE Access
(2023)
Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...
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DOI: https://doi.org/10.1109/access.2023.3310400
Sheemona Joseph C., S. Ganesh, S. Kannadhasan, K. Selvipriya • Journal of Informatics and Web Engineering
(2025)
Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...
DOAJ
Open Access (DOAJ)
DOI: 10.33093/jiwe.2025.4.2.14
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
Bin Li, Hong Fu • Applied Computational Intelligence and Soft Computing
(2018)
An accurate and efficient eye detector is essential for many computer vision applications. In this paper, we present an efficient method to evaluate the eye location from facial images. First, a group of candidate regions with regional extr...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/2018/1439312
Rui Pimentel de Figueiredo, Stefan Nordborg Eriksen, Ignacio Rodriguez, Simon Bøgh • Automation
(2025)
Corrosion, a naturally occurring process leading to the deterioration of metallic materials, demands diligent detection for quality control and the preservation of metal-based objects, especially within industrial contexts. Traditional tech...
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Open Access (DOAJ)
DOI: 10.3390/automation6020023
SHA Yuyang, LU Jingtao, DU Haofan, ZHAI Xiaobing, MENG Weiyu, LIAN Xu, LUO Gang, LI Kefeng • Jisuanji gongcheng
(2025)
Image segmentation is a crucial technology for environmental perception, and it is widely used in various scenarios such as autonomous driving and virtual reality. With the rapid development of technology, computer vision-based blind guidin...
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Open Access (DOAJ)
DOI: 10.19678/j.issn.1000-3428.0068674
Dang Minh Tan, Le-Minh Kieu • IATSS Research
(2023)
This paper introduces a new visual dataset and framework to facilitate computer-vision-based traffic monitoring in high density, mixed and lane-free traffic (TRAMON). While there are advanced deep learning algorithms that can detect and tra...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.iatssr.2023.10.001
V. G. Dhanya, Anakkallan Subeesh, Nand Lal Kushwaha, Dinesh Kumar Vishwakarma et al. • Artificial Intelligence in Agriculture
(2022)
The agriculture industry is undergoing a rapid digital transformation and is growing powerful by the pillars of cutting-edge approaches like artificial intelligence and allied technologies. At the core of artificial intelligence, deep learn...
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DOI: https://doi.org/10.1016/j.aiia.2022.09.007
Yaguang Guo, Qi Zou, Lu Jin • IET Computer Vision
(2021)
Abstract Because of the popularisation of high‐resolution images, detecting objects in these images quickly and accurately has attracted increasing attention in recent studies. Current convolutional neural networks (CNN)‐based detection met...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/cvi2.12042