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Image Recognition Technology in Smart Agriculture: A Review of Current Applications Challenges and Future Prospects. Processes 13: 1402.
DOI: 10.3390/pr13051402
Leveraging knowledge distillation for lightweight and interpretable deep learning in Ethiopian medicinal plant classification. Intelligent Systems with Applications 30: 200638.
DOI: 10.1016/j.iswa.2026.200638
FSUNet: lightweight full-scale information fusion UNet for seed coat thickness measurement. Cogent Food & Agriculture 10: .
DOI: 10.1080/23311932.2024.2424928
Rice Leaf Nutrient Deficiency Classification System Using CAR-Capsule Network. IEEE Access 12: 169518.
DOI: 10.1109/ACCESS.2024.3498606
Enhancing deep convolutional neural network models for orange quality classification using MobileNetV2 and data augmentation techniques. Journal of Algorithms & Computational Technology 19: .
DOI: 10.1177/17483026241309070
Spectral-Spatial Fusion for Soybean Quality Evaluation Using Hyperspectral Imaging. AgriEngineering 7: 274.
DOI: 10.3390/agriengineering7090274
A systematic review of deep learning applications for rice disease diagnosis: current trends and future directions. Frontiers in Computer Science 6: .
DOI: 10.3389/fcomp.2024.1452961
Indigenous wood species classification using a multi-stage deep learning with grad-CAM explainability and an ensemble technique for Northern Bangladesh. PLOS One 20: e0328102.
DOI: 10.1371/journal.pone.0328102
MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism. Frontiers in Artificial Intelligence 8: .
DOI: 10.3389/frai.2025.1498025
BorB: A Novel Image Segmentation Technique for Improving Plant Disease Classification With Deep Learning Models. IEEE Access 13: 71822.
DOI: 10.1109/ACCESS.2025.3563160
Rice Plant Disease Diagnosis Using SqueezeNet and Deep Transfer Learning. Journal of Phytopathology 173: .
DOI: 10.1111/jph.70092
Semantic Segmentation of Rice Fields in Sub-Meter Satellite Imagery Using an HRNet-CA-Enhanced DeepLabV3+ Framework. Remote Sensing 17: 2404.
DOI: 10.3390/rs17142404
Quality Grading of Dried Abalone Using an Optimized VGGNet. Applied Sciences 14: 5894.
DOI: 10.3390/app14135894
PapNet: An AI-Driven Approach for Early Detection and Classification of Papaya Leaf Diseases. Applied Fruit Science 67: .
DOI: 10.1007/s10341-025-01466-9
A Comparative Analysis on the Classification of Pineapple Varieties Using Thermal Imaging Coupled With Transfer Learning. Journal of Food Science 90: .
DOI: 10.1111/1750-3841.70530
Deep learning-based phenotyping of lettuce diseases using Efficient-FBM-FRMNet for precision agriculture. Frontiers in Plant Science 16: .
DOI: 10.3389/fpls.2025.1704647
VGG‐EffAttnNet: Hybrid Deep Learning Model for Automated Chili Plant Disease Classification Using VGG16 and EfficientNetB0 With Attention Mechanism. Food Science & Nutrition 13: .
DOI: 10.1002/fsn3.70653
A deep learning-based bruise detection model for peaches using the NIR imaging dataset. European Food Research and Technology 251: 3847.
DOI: 10.1007/s00217-025-04875-y
Attention mechanism‐based ultralightweight deep learning method for automated multi‐fruit disease recognition system. Agronomy Journal 117: .
DOI: 10.1002/agj2.70035
Revival of Muslin by Phuti Karpas plant identification with convolution neural network. Array 27: 100428.
DOI: 10.1016/j.array.2025.100428
RiceLeafClassifier‐v1.0: A Quantized Deep Learning Model for Automated Rice Leaf Disease Detection and Edge Deployment. Engineering Reports 7: .
DOI: 10.1002/eng2.70231
Optimizing Pear Leaf Disease Detection Through PL-DenseNet. Applied Fruit Science 67: .
DOI: 10.1007/s10341-025-01265-2
Time-Sensitive Bruise Detection in Plums Using PlmNet with Transfer Learning. Procedia Computer Science 257: 127.
DOI: 10.1016/j.procs.2025.03.019
Exploring deep learning and data requirements through image classification of Erigeron annuus and Erigeron philadelphicus. BMC Research Notes 19: .
DOI: 10.1186/s13104-026-07719-4
Deep learning-based classification of lavender for enhanced cultivation and essential oil quality management. Journal of Essential Oil Bearing Plants 28: 1063.
DOI: 10.1080/0972060X.2025.2576649
SAUFCMC-OSCN: deep learning framework with enhanced kookaburra optimization for high-precision black pepper leaf disease classification. International Journal of Modelling and Simulation : 1.
DOI: 10.1080/02286203.2026.2680221
Transfer Learning-Enhanced Leaf Area Index Retrieval From Landsat Surface Reflectance Data. IEEE Transactions on Geoscience and Remote Sensing 64: 4413718.
DOI: 10.1109/TGRS.2026.3715202
SiaRDFNet: Leveraging Siamese Architecture With ResNet‐DenseNet Fusion for Accurate Root Disease Classification. Journal of Field Robotics 43: 1524.
DOI: 10.1002/rob.70103
A Dual-Branch U-Net for Staple Crop Classification in Complex Scenes. Remote Sensing 17: 726.
DOI: 10.3390/rs17040726
RGB‐Based Deep Learning for Freeze Damage Detection in Strawberry: Comparing Scratch and Transfer Learning Approaches on Custom Data. Plant Direct 9: .
DOI: 10.1002/pld3.70124
A Lightweight and High-Performance YOLOv5-Based Model for Tea Shoot Detection in Field Conditions. Agronomy 15: 1122.
DOI: 10.3390/agronomy15051122
Next-generation approach to skin disorder prediction employing hybrid deep transfer learning. Frontiers in Big Data 8: .
DOI: 10.3389/fdata.2025.1503883
Research on agricultural disease recognition methods based on very large Kernel convolutional network-RepLKNet. Scientific Reports 15: .
DOI: 10.1038/s41598-025-01553-7
TikogAI: A Feature-Engineered CNN Model for Classifying Indigenous Tikog Leaves in Banig Weaving. Journal of Innovative Image Processing 7: 362.
DOI: 10.36548/jiip.2025.2.006
ResNet-ViT-SVM: A new hybrid architecture proposal and experimental comparisons on date fruit. Journal of Food Composition and Analysis 148: 108519.
DOI: 10.1016/j.jfca.2025.108519
Papaya Leaf Disease Classification Using Pre-trained Deep Learning Models: A Comparative Study. Applied Fruit Science 67: .
DOI: 10.1007/s10341-025-01533-1
Efficient Adaptive Incremental Learning for Fruit and Vegetable Classification. Agronomy 14: 1275.
DOI: 10.3390/agronomy14061275
Harnessing deep learning for wheat variety classification: a convolutional neural network and transfer learning approach. Journal of the Science of Food and Agriculture 105: 6692.
DOI: 10.1002/jsfa.14378
Y-HRNet: Research on multi-category cherry tomato instance segmentation model based on improved YOLOv7 and HRNet fusion. Computers and Electronics in Agriculture 227: 109531.
DOI: 10.1016/j.compag.2024.109531
Deep Learning Models for Defect Identification in Oryza sativa Rice Grains: A Comparative Study. AgriEngineering 8: 252.
DOI: 10.3390/agriengineering8060252
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DOI: 10.1590/1678-4324-2025241032
Deep learning-based classification of alfalfa varieties: A comparative study using a custom leaf image dataset. MethodsX 13: 103051.
DOI: 10.1016/j.mex.2024.103051
Improved crop row detection by employing attention-based vision transformers and convolutional neural networks with integrated depth modeling for precise spatial accuracy. Smart Agricultural Technology 11: 100934.
DOI: 10.1016/j.atech.2025.100934
Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection. IEEE Access 13: 105888.
DOI: 10.1109/ACCESS.2025.3579074
Mushroom image classification and recognition based on improved ConvNeXt V2. Journal of Food Science 90: .
DOI: 10.1111/1750-3841.70133
Comparative Analysis of CNN Architectures with Optuna-Assisted Hyperparameter Optimization for Classifying Drought-Stressed Soybean Seeds. Food Analytical Methods 19: .
DOI: 10.1007/s12161-026-03204-7
PTL-Inception: Integrating Deep Learning and Taxonomy for Desert Plant Classification. Diversity 17: 806.
DOI: 10.3390/d17110806
Comparison of deep learning models in automatic classification of coffee bean species. PeerJ Computer Science 11: e2759.
DOI: 10.7717/peerj-cs.2759
Neural Network‐Based Study for Rice Leaf Disease Recognition and Classification: A Comparative Analysis Between Feature‐Based Model and Direct Imaging Model. Food Science & Nutrition 13: .
DOI: 10.1002/fsn3.71350
DSA-net: a lightweight and efficient deep learning-based model for pea leaf disease identification. Frontiers in Plant Science 16: .
DOI: 10.3389/fpls.2025.1642453
Detection of imidacloprid in spinach using spectral technology and machine learning. Journal of Food Composition and Analysis 149: 108682.
DOI: 10.1016/j.jfca.2025.108682
Pattern Classification of an Onion Crop (Allium Cepa) Field Using Convolutional Neural Network Models. Agronomy 14: 1206.
DOI: 10.3390/agronomy14061206
Optimized DINO model for accurate object detection of sesame seedlings and weeds. Scientific Reports 15: .
DOI: 10.1038/s41598-025-96826-6
Soybean Seeds Quality Identification Through Image Classification Using Machine Learning. 2026 5th OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 5.0 : 1.
DOI: 10.1109/OTCON69332.2026.11629833
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DOI: 10.1109/ECCE64574.2025.11014047
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DOI: 10.1109/ICISCT64202.2024.10956712
Feature Engineering and Optimization of Convolutional Neural Network in Classifying Tikog Leaf for Banig Weaving Industry. 2025 25th International Conference on Control Systems and Computer Science (CSCS) : 231.
DOI: 10.1109/CSCS66924.2025.00042
A Database for Soybean Seed Classification. 2024 37th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) : 1.
DOI: 10.1109/SIBGRAPI62404.2024.10716268
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DOI: 10.1109/ISADES69945.2026.11608227
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DOI: 10.1109/ISADES69945.2026.11608190
Data Science and Network Engineering. Chapter 9: 109.
DOI: 10.1007/978-981-97-8336-6_9
Modern Intelligent Techniques for Image Processing. chapter 2: 37.
DOI: 10.4018/979-8-3693-9045-0.ch002
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