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Geo-Temporal Selective Approach for Dynamic Depth Estimation in Outdoor Object Detection and Distance Measurement

Muhammad Faseeh, Misbah Bibi, Murad Ali Khan, Atif Rizwan et al. • IEEE Access (2024)

Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3485089

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

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

Estimating Black Oat Biomass Using Digital Surface Models and a Vegetation Index Derived from RGB-Based Aerial Images

Lucas Renato Trevisan, Lisiane Brichi, Tamara Maria Gomes, Fabrício Rossi • Remote Sensing (2023)

Responsible for food production and industry inputs, agriculture needs to adapt to worldwide increasing demands and environmental requirements. In this scenario, black oat has gained environmental and economic importance since it can be use...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs15051363

Fruit freshness detection based on multi-task convolutional neural network

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...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.crfs.2024.100733

Computer vision vs. human vision

Bo Zhang • IEEE International Conference on Cognitive Informatics (2010)

In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. Bu...

OPENALEX DOI: https://doi.org/10.1109/coginf.2010.5599750

Performance Benchmarking: Pre-trained Models and Custom Convolutional Neural Networks in Deep Learning

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

TransCat: a hybrid CNN-transformer network with KAN for medical image segmentation

Jin Wang, Zhenghua Yang, Dongming Zhou, Dongming Zhou et al. • Frontiers in Bioinformatics (2026)

Medical image segmentation is a fundamental task in computer vision and plays an important role in clinical diagnosis and treatment planning. Existing methods are mainly built on either convolutional neural networks (CNNs) or Transformer-ba...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbinf.2026.1849059

Lightweight Road Image Segmentation Algorithm Based on Multi-Scale Feature Fusion for Blind Guiding Scenarios

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...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0068674

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access (2019)

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2932037

Deep Learning for Computer Vision: A Brief Review

Ksheera R Shetty, Vaibhav S Soorinje, Prinson Dsouza, Swasthik • International Journal of Advanced Research in Science Communication and Technology (2022)

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...

OPENALEX cc-by DOI: https://doi.org/10.48175/ijarsct-2898

Deep learning based computer vision approaches for smart agricultural applications

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...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.aiia.2022.09.007

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