A5023256790- Biometric Identification and Security
- Retinal Imaging and Analysis
- AI in cancer detection
- Dermatoglyphics and Human Traits
- Face recognition and analysis
- Advanced Neural Network Applications
- Radiomics and Machine Learning in Medical Imaging
- User Authentication and Security Systems
- Visual Attention and Saliency Detection
- Medical Image Segmentation Techniques
- COVID-19 diagnosis using AI
- Retinal and Optic Conditions
- Digital Imaging for Blood Diseases
- Brain Tumor Detection and Classification
- Retinal Diseases and Treatments
- Advanced Image and Video Retrieval Techniques
- Vehicle License Plate Recognition
- Video Analysis and Summarization
- Text and Document Classification Technologies
- Anomaly Detection Techniques and Applications
- Digital Media Forensic Detection
- Forensic and Genetic Research
- Human Pose and Action Recognition
- Artificial Intelligence in Healthcare
- Lung Cancer Diagnosis and Treatment
Gdańsk University of Technology
2022-2024
South China University of Technology
2021-2023
Shandong University
2018-2020
Shandong University of Science and Technology
2018
The primary objective of this study is to develop an advanced, automated system for the early detection and classification leaf diseases in potato plants, which are among most cultivated vegetable crops worldwide. These diseases, notably late blight caused by Alternaria solani Phytophthora infestans, significantly impact quantity quality global production. We hypothesize that integration Vision Transformer (ViT) ResNet-50 architectures a new model, named EfficientRMT-Net, can effectively...
In recent years, a lot of attention has been paid to using radiology imaging automatically find COVID-19. (1) Background: There are now number computer-aided diagnostic schemes that help radiologists and doctors perform COVID-19 tests quickly, accurately, consistently. (2) Methods: Using chest X-ray images, this study proposed cutting-edge scheme for the automatic recognition pneumonia. First, pre-processing method based on Gaussian filter logarithmic operator is applied input (CXR) images...
Diabetic retinopathy (DR) is a complication of diabetes and known as visual impairment, diagnosed in various ethnicities the working-age population worldwide. Fundus angiography widely applicable modality used by ophthalmologists computerized applications to detect DR-based clinical features such microaneurysms (MAs), hemorrhages (HEMs), exudates (EXs) for early screening DR. images are usually acquired using funduscopic cameras varied light conditions angles. Therefore, these prone...
Hypertensive retinopathy (HR) is a serious eye disease that causes the retinal arteries to change. This change mainly due fact of high blood pressure. Cotton wool patches, bleeding in retina, and artery constriction are affected lesions HR symptoms. An ophthalmologist often makes diagnosis eye-related diseases by analyzing fundus images identify stages symptoms HR. The likelihood vision loss can significantly decrease initial detection In past, few computer-aided diagnostics (CADx) systems...
Computed tomography (CT) scans, or radiographic images, were used to aid in the early diagnosis of patients and detect normal abnormal lung function human chest. However, lungs infected with coronavirus disease 2019 (COVID-19) was made more accurately from CT scan data than a swab test. This study uses chest radiography pictures identify categorize lungs, opacities, COVID-19-infected viral pneumonia (often called pneumonia). In past, several CAD systems using image processing, ML/DL, other...
Abstract The field of medical image segmentation, particularly in the context brain tumor delineation, plays an instrumental role aiding healthcare professionals with diagnosis and accurate lesion quantification. Recently, Convolutional Neural Networks (CNNs) have demonstrated substantial efficacy a range computer vision tasks. However, notable limitation CNNs lies their inadequate capability to encapsulate global distal semantic information effectively. In contrast, advent Transformers,...
Hypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness directly related the severity and duration hypertension. It critical identify analyze HR at an early stage avoid blindness. There are presently only few computer-aided systems (CADx) designed recognize HR. Instead, those concentrated on collecting features from many retinopathy-related lesions then classifying them using traditional machine learning algorithms. Consequently,...
Although deep learning-based techniques for salient object detection have considerably improved over recent years, estimated saliency maps still exhibit imprecise predictions owing to the internal complexity and indefinite boundaries of objects varying sizes. Existing methods emphasize design an exemplary structure integrate multi-level features by employing multi-scale attention modules filter regions from cluttered scenarios. We propose a network based on three novel contributions. First,...
Salient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects an image. To address the challenges of gridding issues feature dilution effects commonly encountered SOD, we propose sophisticated context-aware middle-layer guidance network (CMGNet). CMGNet incorporates central-layer module (CCGM), which utilizes cost-effective large kernels depth-wise convolutions with embedded parallel channel attentions...
As a secure and reliable biometric trait, finger vein recognition (FVR) can be employed to verify the individuals in real-time applications. However, pattern of is unclear some images due light scattering by skin non-uniform illumination, which deteriorates performance FVR system. To deal with image quality problem, novel finger-vein assessment method an enhancement are proposed. The proposed Scheme based on two folds: (i) Image Quality Assessment, (ii) Enhancement. First, assessed decision...