People routinely capture photos and videos to document their daily experiences, with such visual media frequently regarded as reliable sources of evidence. The proliferation of social networking platforms, digital photography technologies, and image ...
Real-time detecting and identifying impurities in wheat grain mass is crucial for wheat storage silos, flour mills and modern combines. Depending on the detection objectives, accuracy is typically prioritized in laboratory-based applications, whereas...
The issue of generating a natural language explanation of images to define their visual content has garnered significant attention in computer vision (CV) and natural language processing (NLP). It is driven by applications such as image virtual assis...
Deep Learning methods have become a powerful tool in medical imaging, with great potential to improve diagnostic accuracy and support early disease detection. This is especially critical for breast cancer, one of the most common cancers among women, ...
BACKGROUND: Accurate quantification of the Ki-67 proliferation index is essential for breast cancer prognosis and treatment planning. Current automated methods, including classical and deep learning approaches based on cell detection or segmentation,...
The key objective of producing artificial digital data is to closely mimic real data. However, because of improper use by malevolent users, the legitimacy of this kind of digital content may be under threat in society. Deepfake techniques, which repl...
Accurate and early diagnosis of malaria from peripheral blood smear images remains a critical challenge in healthcare, particularly in resource-limited settings. In this work, we propose an optimized convolutional neural network (CNN) framework enhan...
Agricultural production is still quite susceptible to plant diseases, despite the fact that it is essential to both economic growth and food security. Yellow rust can lower wheat yields by 20-30%, red rust by 5-10%, and anthracnose by up to 60% in cr...
Brain tumors (BTs) pose a serious threat to human health, and the optimized treatment and results depend on early and accurate detection. Although MRIs and other medical imaging technologies provide insightful information, it is still difficult to de...
Data scarcity remains a major obstacle to the application of deep learning techniques in medical imaging, particularly for rare neurodegenerative diseases. This study investigates the use of denoising diffusion probabilistic models (DDPMs) to generat...
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