1. Medical Image Segmentation
1.1. Research U-Net Image Segmentation
1.1.1. 2023
1.1.1.1. U-Net
1.1.1.2. Q1
1.1.1.2.1. Scientific Reports: Using DUCK‑Net for polyp image segmentation
1.1.1.2.2. IEEE Transaction: META-Unet: Multi-Scale Efficient Transformer Attention Unet for Fast and High-Accuracy Polyp Segmentation
1.1.1.2.3. IEEE Journal of Translational Engineering in Health and Medicine: TransU²-Net: An Effective Medical Image Segmentation Framework Based on Transformer and U²-Net
1.1.1.2.4. Scientific Reports: A deep network embedded with rough fuzzy discretization for OCT fundus image segmentation
1.1.1.2.5. BMC Bioinformatics: EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation
1.1.1.3. Q2
1.1.1.3.1. Image and Vision Computing: Multi parallel U-net encoder network for effective polyp image segmentation
1.1.1.3.2. Electronics: A Novel Fuzzy DBNet for Medical Image Segmentation
1.1.1.3.3. U-Net-ASPP: U-Net based on atrous spatial pyramid pooling model for medical image segmentation in COVID-19
1.1.1.4. Q3
1.1.1.4.1. Measurement: Sensors, Segmentation of skin cancer using Fuzzy U-network via deep learning
1.1.2. 2022
1.1.2.1. Q1
1.1.2.1.1. IEEE: CU-Net: A New Improved Multi-Input Color U-Net Model for Skin Lesion Semantic Segmentation
1.2. Optimization Image Segmentation
1.2.1. Fuzzy Image Segmentation
1.2.1.1. 2023
1.2.1.1.1. Q1
1.2.1.2. 2022
1.2.1.2.1. Q1
1.2.1.2.2. Q2
1.2.1.3. 2021
1.2.1.3.1. Q1
1.2.2. Fuzzy Metaheuristics
1.2.2.1. Swarm
1.2.2.1.1. Particle Swarm Optimization
1.2.2.1.2. Ant Colony
1.2.2.2. Evolutionary
1.2.2.2.1. Genetic Algorithm
1.2.2.3. Physics Based
1.2.2.3.1. simulated annealing