A5026007448- Advanced Photocatalysis Techniques
- Copper-based nanomaterials and applications
- AI in cancer detection
- ZnO doping and properties
- Radiomics and Machine Learning in Medical Imaging
- Digital Imaging for Blood Diseases
- Gas Sensing Nanomaterials and Sensors
- Traffic Prediction and Management Techniques
- Cell Image Analysis Techniques
- Image Processing Techniques and Applications
- Ga2O3 and related materials
- Medical Image Segmentation Techniques
- TiO2 Photocatalysis and Solar Cells
- Transition Metal Oxide Nanomaterials
- Granular flow and fluidized beds
- Iron oxide chemistry and applications
- Luminescence Properties of Advanced Materials
- Microfluidic and Bio-sensing Technologies
- Microfluidic and Capillary Electrophoresis Applications
- Colorectal Cancer Screening and Detection
- Advancements in Battery Materials
- Lanthanide and Transition Metal Complexes
- Human Mobility and Location-Based Analysis
- Advanced Battery Materials and Technologies
- Handwritten Text Recognition Techniques
Tongmyong University
2015-2024
Zero to Three
2017
Pusan National University
2003
Diagnosis of pathologies using histopathological images can be time-consuming when many with different magnification levels need to analyzed. State-of-the-art computer vision and machine learning methods help automate the diagnostic pathology workflow thus reduce analysis time. Automated systems also more efficient accurate, increase objectivity diagnosis by reducing operator variability. We propose a multi-scale input multi-feature network (MSI-MFNet) model, which learn overall structures...
The nanostructured In2O3 thin films were deposited on Si n-type (1 0 0) substrates by reactive thermal evaporation. structural, morphological, and oxidation states of the investigated using x-ray diffraction, scanning electron microscopy, atomic force photoelectron spectroscopy. optical properties analyzed UV–vis spectroscopy, Raman photoluminescence showed c-In2O3 crystalline nanostructures with a preferred diffraction peak (2 2 2). truncated icosahedron shape's morphology transmittance 85%...
Chronic pain is a multifaceted condition that has yet to be fully comprehended. It frequently linked with range of disorders, particularly osteoarthritis (OA), which arises from the progressive deterioration protective cartilage cushions bone endings over time.
An automatic pathological diagnosis is a challenging task because histopathological images with different cellular heterogeneity representations are sometimes limited. To overcome this, we investigated how the holistic and local appearance features limited information can be fused to enhance analysis performance. We propose an unsupervised deep learning model for whole-slide image diagnosis, which uses stacked autoencoders simultaneously feeding multiple-image descriptors such as histogram...