Latest Research in Computer Vision and Pattern Recognition

Top Research Topics in Computer Vision and Pattern Recognition

• Computer Vision and Pattern Recognition — 4 papers
• Wood and Agarwood Research — 3 papers
• Smart Agriculture and AI — 1 papers
• Remote Sensing and LiDAR Applications — 1 papers
• Insect and Pesticide Research — 1 papers
• Lepidoptera: Biology and Taxonomy — 1 papers
• Morphological variations and asymmetry — 1 papers
• Insect and Arachnid Ecology and Behavior — 1 papers
• Neurobiology and Insect Physiology Research — 1 papers
• Water Quality Monitoring Technologies — 1 papers

Highest-Cited Papers

1. Few-Shot Ordinal Learning for Day-Wise Freshness Estimation with Hyperspectral Fish Images
2. Multi-Model Comparative Study for Bark-Texture Based Tree Species Classification Using Custom Indian Tree Species Dataset
3. Multi-Model Comparative Study for Bark-Texture Based Tree Species Classification Using Custom Indian Tree Species Dataset
4. LeaDeiT: data-efficient image transformer with knowledge distillation for leather species identification
5. A learning-dynamics-driven framework for robust small-object detection in complex field environments: YOLOv11l-AGRI-EMA framework
6. Assessing Applications of Self-Supervised Learning for Tree Species Classification from LiDAR Point Clouds
7. Deep learning-based hierarchical insect classification using camera trap imagery
8. Development and Evaluation of a Low‐Cost, Semi‐Automated Camera Trap for Surveying Bumble Bee Communities
9. Comparing deep learning models for butterfly and moth (Lepidoptera) species identification
10. Small-Pollinator Detection in Cluttered Field Video
11. Garryanalyzer: A morphometric workflow and open‐source ImageJ plug‐in for quantitative morphological analysis of Pacific Northwest Quercus leaves
12. Geographic Classification of Social Bees Using Automated Wing Pattern Analysis
13. Model evaluation for automated scoring of electropenetrography waveform data from mosquitoes
14. ReViTA-Unet: An Enhanced Semantic Segmentation Model for Automated Morphometric Analysis of Macrobrachium rosenbergii
15. Automated identification of Ichneumonoidea wasps via YOLO-based deep learning: Integrating HiresCam for Explainable AI
16. Deep Learning Pipeline for the Identification of Ground Beetles (Carabidae) in New Zealand