A5102010598- Digital Imaging for Blood Diseases
- COVID-19 diagnosis using AI
- Remote-Sensing Image Classification
- Image Processing Techniques and Applications
- Remote Sensing and Land Use
- Remote Sensing and LiDAR Applications
- Remote Sensing in Agriculture
- Advanced Neural Network Applications
- Hydrology and Sediment Transport Processes
- Flood Risk Assessment and Management
- Image Retrieval and Classification Techniques
- Image Enhancement Techniques
- AI in cancer detection
- Immunotherapy and Immune Responses
- Water Quality Monitoring Technologies
Hubei University of Technology
2024
Building change detection (BCD) is essential for urban dynamic measurement. Deep learning has demonstrated significant potential in image processing, providing powerful feature extraction capabilities BCD tasks. However, existing methods do not adequately mine multiscale information and ignore the importance of alignment, leading to an inadequate representation internal structure. Therefore, we propose a hybrid attention-aware Transformer network (HATNet) designed effectively extract...
Remote sensing (RS) image change detection methods based on deep learning such as convolutional neural networks (CNN) and transformers are still spatial domain-based processing by nature, their accuracy is strongly affected chromatic aberration due to imaging time, shadows caused lighting conditions, object confusion other disturbances. In this study, we revisit (CD) from a signal perspective, framing it the task of consistency distributional features two 2D signals. We aim extract primary...
Reactive lymphocytes may indicate diseases such as viral infections. Identifying these abnormal is crucial for disease diagnosis. Currently, reactive are mainly manually identified by pathological experts with microscopes and morphological knowledge, which time-consuming laborious. Some studies have used convolutional neural networks (CNNs) to identify peripheral blood leukocytes, but there limitations in the small receptive field of model. Our model introduces a transformer based on CNN,...
ABSTRACT Leukemia is a hematological malignancy that significantly impacts the human immune system. Early detection helps to effectively manage and treat cancer. Although deep learning techniques hold promise for early of blood disorders, their effectiveness often limited by physical constraints available datasets deployed devices. For this investigation, we collect an excellent‐quality dataset 17,826 morphological bone marrow cell images from 85 patients with lymphoproliferative neoplasms....