Latest Research in Advanced Neural Network Applications

Top Research Topics in Advanced Neural Network Applications

• Smart Agriculture and AI — 60 papers
• Computer Vision and Pattern Recognition — 25 papers
• Advanced Neural Network Applications — 5 papers
• Robotics — 4 papers
• Remote Sensing in Agriculture — 4 papers
• Remote Sensing and LiDAR Applications — 4 papers
• Spectroscopy and Chemometric Analyses — 3 papers
• Industrial Vision Systems and Defect Detection — 3 papers
• Allergic Rhinitis and Sensitization — 2 papers
• Leaf Properties and Growth Measurement — 2 papers

Highest-Cited Papers

1. A cloud-integrated deep learning system for weed detection using Jetson Nano
2. YOLOv8-EMA-P2: An Enhanced Deep Learning Framework for Wheat Grain Detection and Counting from Single-Spike Images
3. A learning-dynamics-driven framework for robust small-object detection in complex field environments: YOLOv11l-AGRI-EMA framework
4. FruitDet: A Multi-Module Lightweight Detector for Young Apple Fruits Under Day–Night Orchard Conditions
5. A two-stage deep learning framework for oil palm fresh fruit bunch ripeness classification toward predictive harvesting in precision agriculture
6. An Automated Population Monitoring Framework for Larus ridibundus in Kunming City Based on Improved YOLOv8 and ByteTrack
7. TMAF-YOLO: A Lightweight Model for In Situ Detection of Tomato Maturity and Defective Fruits in Greenhouses
8. Explainable lightweight deep learning architectures for crop anomaly detection using enhanced Grad-CAM and transfer learning
9. A Non-Destructive Acoustic Tapping System with Deep Learning for Pineapple Juiciness Classification in Postharvest Quality Assessment
10. Deep learning-based body length estimation in soil-dwelling arthropods
11. Oh Deer, How Should I Handle This? Seasonal Priors for Selective Wildlife Annotation and Classification
12. Promptable Animal Pose Tracking Across Species
13. Foreseeing the Invisible: Amodal Reconstruction of Leaf Fossil Images
14. Vision-Based Counting of Horticultural Seeds Using ViT-UNet Density Regression for Post-Harvest Quality Assessment
15. MC-RT-DETR: A Lightweight Real-Time Cotton Top Bud Detection Model Based on Improved RT-DETR
16. Improved YOLOv8 Weed Segmentation Method Based on Dual-ViT
17. Self-Supervised Multimodal Learning for Preharvest and Postharvest Fruit Quality Assessment Using Images and Environmental Sensors
18. DSA-UNet: Attention-Integrated and High-Frequency Feature-Preserved U-Net for Fuding White Tea Bud Segmentation
19. MBFFN: A Multi-Backbone Feature Fusion Network for Fine-Grained Plant Species Classification
20. A Comparative Evaluation of Deep Learning Architectures for Weed Classification, with an Exploratory Out-of-Distribution Analysis of Albanian Field Images