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  1. OBBStacking: An Ensemble Method for Remote Sensing Object Detection
  2. CVM-Cervix: A hybrid cervical Pap-smear image classification framework using CNN, visual transformer and multilayer perceptron
  3. GasHisSDB: A new gastric histopathology image dataset for computer aided diagnosis of gastric cancer
  4. Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: From convolutional neural networks to visual transformers
  5. A hierarchical conditional random field-based attention mechanism approach for gastric histopathology image classification
  6. LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation
  7. A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development
  8. A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis
  9. Intelligent Gastric Histopathology Image Classification Using Hierarchical Conditional Random Field based Attention Mechanism
  10. Microscopic Image Augmentation Using an Enhanced WGAN
  11. A Comparison of Segmentation Methods in Gastric Histopathology Images
  12. A State-of-the-art Review for Gastric Histopathology Feature Extraction Methods
  13. Gastric histopathology image segmentation using a hierarchical conditional random field
  14. A hierarchical conditional random field model for multi-object segmentation in gastric histopathology images
  15. A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks
  16. A Multiscale CNN‐CRF Framework for Environmental Microorganism Image Segmentation