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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

Mapping the Unknown: Using Incomplete Evidence to Craft Digital Three-Dimensional Models of St Stephen’s

Anthony Masinton, James Jago • British Art Studies (2020)

Crafting a digital reconstruction of a lost space is a process of rediscovery and exploration. The nature of the evidence determines the form of the reconstruction, providing a sketch of what is known about the space. The process of reconst...

DOAJ Open Access (DOAJ) DOI: 10.17658/issn.2058-5462/issue-16/amasinton

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

AutoWindLoc: Precise Localization of Wind Turbines in High-Resolution Orthophotos for Enhanced Registers

J. Middendorf, A. Kelm, S. Frintrop • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2025)

The paper proposes a novel framework for automatically detecting wind turbines in orthophotos, transferring this information to a database, and linking detected turbines to an existing registry to minimize location inaccuracy. This inaccura...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLVIII-M-7-2025-35-2025

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

VISION-LINK AI Smart Glass: An Edge-Cloud Wearable AI System for Workflow Automation and Digital Inclusion in Emerging Economies

Buhari Salisu • International Journal of AI and Advanced Computing (2026)

The rapid advancement of Artificial Intelligence (AI), wearable computing, and Internet of Things (IoT) technologies has significantly transformed digital interactions across various sectors. However, the adoption of smart wearable technolo...

DOAJ Open Access (DOAJ) DOI: 10.5281/zenodo.21981139

AN IMPROVED MASK R-CNN: EXTRACTION OF DOOR AND WINDOW INSTANCES ON VILLAGE BUILDING FAÇADE IMAGES

D. Zhong, D. Zhong, L. He, L. He et al. • ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2023)

Rapid access to the basic structure of village buildings is conducive to the investigation of the load-bearing bodies of village houses and provides data support for disaster assessment and post-disaster rescue and reconstruction. The devel...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-annals-X-1-W1-2023-295-2023

TSER: A Two-Stage Character Segmentation Network With Two-Stream Attention and Edge Refinement

Jinyingming Zhang, Jin Liu, Xiongwei Xu, Peizhu Gong et al. • IEEE Access (2020)

Segmenting characters in an image is a classic yet challenging task in computer vision. Correctly determining boundaries of adhesive characters with various scales and shapes is essential for character segmentation, especially for separatin...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3036545

PAMPAS: real-valued graphical models for computer vision

Michael Isard • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2003)

Probabilistic models have been adopted for many computer vision applications, however inference in high-dimensional spaces remains problematic. As the state-space of a model grows, the dependencies between the dimensions lead to an exponent...

OPENALEX DOI: https://doi.org/10.1109/cvpr.2003.1211410