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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

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

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

Design and Implementation of a Ball-Plate Control System and Python Script for Educational Purposes in STEM Technologies

Vladimir Tudić, Damir Kralj, Josip Hoster, Tomislav Tropčić • Sensors (2022)

This paper presents the process of designing, fabricating, assembling, programming and optimizing a prototype nonlinear mechatronic Ball-Plate System (BPS) as a laboratory platform for engineering education STEM. Due to the nonlinearity and...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22051875

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 and Natural Constraints

C. M. Brown • Science (1984)

Computer vision, the automatic construction of scene descriptions from image input data, has just entered its second decade. Approaches have varied widely, especially in the amounts of symbolic, domain-dependent knowledge and inference that...

OPENALEX DOI: https://doi.org/10.1126/science.224.4655.1299

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

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