Exploring artificial intelligence role in improving service building engagement in sorting
Waste management researchers have identified that the correct disposal of solid waste is
better addressed upstream, where people properly sort their solid waste. Sorting solid waste …
better addressed upstream, where people properly sort their solid waste. Sorting solid waste …
An adaptation of hybrid binary optimization algorithms for medical image feature selection in neural network for classification of breast cancer
The performance of neural network is largely dependent on their capability to extract very
discriminant features supporting the characterization of abnormalities in the medical image …
discriminant features supporting the characterization of abnormalities in the medical image …
Boundary guided network with two-stage transfer learning for gastrointestinal polyps segmentation
S Li, X Tang, B Cao, Y Peng, X He, S Ye… - Expert Systems with …, 2024 - Elsevier
The automated segmentation of polyps plays a crucial role in the early diagnosis and
treatment of gastrointestinal diseases. However, due to the diversity of polyp lesions and …
treatment of gastrointestinal diseases. However, due to the diversity of polyp lesions and …
Multi-level training and testing of CNN models in diagnosing multi-center COVID-19 and pneumonia X-ray images
Featured Application Despite their reported high accuracy, a significant limitation of current
AI-assisted COVID-19 diagnostic models is that they are often trained on datasets sourced …
AI-assisted COVID-19 diagnostic models is that they are often trained on datasets sourced …
A novel deep learning approach (Bi-xBcNet-96) considering green AI to discover breast cancer using mammography images
Clinical decision support systems (CDSSs) can effectively detect illnesses such as breast
cancer (BC) using a variety of medical imaging techniques. BC is a key factor contributing to …
cancer (BC) using a variety of medical imaging techniques. BC is a key factor contributing to …
[HTML][HTML] Concatenated CNN-Based Pneumonia Detection Using a Fuzzy-Enhanced Dataset
Pneumonia is a form of acute respiratory infection affecting the lungs. Symptoms of viral and
bacterial pneumonia are similar. Rapid diagnosis of the disease is difficult, since …
bacterial pneumonia are similar. Rapid diagnosis of the disease is difficult, since …
Classifying chest x-rays for COVID-19 through transfer learning: a systematic review
This study makes a comprehensive assessment of the predominant Transfer Learning (TL)
techniques employed for the classification of COVID-19 cases in Chest X-rays (CXR) …
techniques employed for the classification of COVID-19 cases in Chest X-rays (CXR) …
CoSEF-DBP: Convolution scope expanding fusion network for identifying DNA-binding proteins through bilingual representations
H Zhang, X Yang, P Chen, C Yang, B Chen… - Expert Systems with …, 2025 - Elsevier
Precisely recognizing DNA-binding proteins (DBPs) from sequences is crucial for a profound
comprehension of the mechanisms governing protein-DNA interactions in various cellular …
comprehension of the mechanisms governing protein-DNA interactions in various cellular …
Resnet50 and logistic Gaussian map-based zero-watermarking algorithm for medical color images
Medical image copyright protection is becoming increasingly relevant as medical images
are used more frequently in medical networks and institutions. The traditional embedded …
are used more frequently in medical networks and institutions. The traditional embedded …
C-Hybrid-NET: A self-attention-based COVID-19 screening model based on concatenated hybrid 2D-3D CNN features from chest X-ray images
K Bayoudh, F Hamdaoui, A Mtibaa - Multimedia Tools and Applications, 2024 - Springer
The outbreak of novel coronavirus (2019-nCOV, commonly known as COVID-19) was
declared a global pandemic by the World Health Organization (WHO) in March 2020. An …
declared a global pandemic by the World Health Organization (WHO) in March 2020. An …