Crop Pest Classification Using Deep Learning Techniques: A Review | Paper Citation Record

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This paper cites Food and agriculture organization of the United Nations—F AO.

Crop Pest Classification Using Deep Learning Techniques: A Review Food and agriculture organization of the United Nations—F AO

Reference 1

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This paper cites Using Deep Learning for Image-Based Plant Disease Detection.

Crop Pest Classification Using Deep Learning Techniques: A Review Using Deep Learning for Image-Based Plant Disease Detection

Reference 2

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This paper cites Using image augmentation techniques and convolutional neural networks to identify insect infestations on tomatoes.

Crop Pest Classification Using Deep Learning Techniques: A Review Using image augmentation techniques and convolutional neural networks to identify insect infestations on tomatoes

Reference 3

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This paper cites Deep Learning for Image-Based Cassava Disease Detection.

Crop Pest Classification Using Deep Learning Techniques: A Review Deep Learning for Image-Based Cassava Disease Detection

Reference 4

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Crop Pest Classification Using Deep Learning Techniques: A Review An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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This paper cites Improved Lightweight YOLOv8 Model for Rice Disease Detection in Multi-Scale Scenarios.

Crop Pest Classification Using Deep Learning Techniques: A Review Improved Lightweight YOLOv8 Model for Rice Disease Detection in Multi-Scale Scenarios

Reference 6

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This paper cites CactiViT: Image-based smartphone application and transformer network for diagnosis of cactus cochineal.

Crop Pest Classification Using Deep Learning Techniques: A Review CactiViT: Image-based smartphone application and transformer network for diagnosis of cactus cochineal

Reference 7

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This paper cites IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition.

Crop Pest Classification Using Deep Learning Techniques: A Review IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition

Reference 8

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Observation fabdaf36-ddb7-449f-bb76-7f254d7c8cbb · outbound

This paper cites A systematic review on automatic insect detection using deep learning.

Crop Pest Classification Using Deep Learning Techniques: A Review A systematic review on automatic insect detection using deep learning

Reference 9

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Observation ca449a51-8cae-4f84-8d7c-a3735c110b6a · outbound

This paper cites Pest Localization Using YOLOv5 and Classification Based on Quantum Convolutional Network.

Crop Pest Classification Using Deep Learning Techniques: A Review Pest Localization Using YOLOv5 and Classification Based on Quantum Convolutional Network

Reference 10

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Observation 62d14ab6-f752-43e0-83c9-7d4652b26ab2 · outbound

This paper cites Pest-ConFormer: A Hybrid CNN-Transformer Architecture for Large-Scale Multi-Class Crop Pest Recognition.

Crop Pest Classification Using Deep Learning Techniques: A Review Pest-ConFormer: A Hybrid CNN-Transformer Architecture for Large-Scale Multi-Class Crop Pest Recognition

Reference 11

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Observation c14d66f9-33f6-4c3f-a62e-1bcc2a3fe2d1 · outbound

This paper cites A transformer-based model with feature compensation and local information enhancement for end-to-end pest detection.

Crop Pest Classification Using Deep Learning Techniques: A Review A transformer-based model with feature compensation and local information enhancement for end-to-end pest detection

Reference 12

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Observation d0497157-8958-4ae7-ab99-a08a9c8d40e9 · outbound

This paper cites YOLOv7-PSAFP: Crop pest and disease detection based on improved YOLOv7.

Crop Pest Classification Using Deep Learning Techniques: A Review YOLOv7-PSAFP: Crop pest and disease detection based on improved YOLOv7

Reference 13

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This paper cites Tomato Diseases and Pests Detection Based on Improved Yolo V3 Convolutional Neural Network.

Crop Pest Classification Using Deep Learning Techniques: A Review Tomato Diseases and Pests Detection Based on Improved Yolo V3 Convolutional Neural Network

Reference 14

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Observation cd9a018c-45e6-4032-8350-c36755b82c98 · outbound

This paper cites Pest detection and classification in peanut crops using CNN, MFO, and EViTA algorithms.

Crop Pest Classification Using Deep Learning Techniques: A Review Pest detection and classification in peanut crops using CNN, MFO, and EViTA algorithms

Reference 15

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Observation 424eb241-3a50-4692-a32b-3b0142fdca12 · outbound

This paper cites Pest Detection and Classification in Peanut Crops Using CNN and EViTA Algorithms.

Crop Pest Classification Using Deep Learning Techniques: A Review Pest Detection and Classification in Peanut Crops Using CNN and EViTA Algorithms

Reference 16

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Observation e83ca581-f89b-401e-8796-913d9eb6d1c2 · outbound

This paper cites Microscopic Insect Pest Detection in Tea Plantations: Improved YOLOv8 Model Based on Deep Learning.

Crop Pest Classification Using Deep Learning Techniques: A Review Microscopic Insect Pest Detection in Tea Plantations: Improved YOLOv8 Model Based on Deep Learning

Reference 17

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This paper cites Tea insect pests classification based on artificial neural networks.

Crop Pest Classification Using Deep Learning Techniques: A Review Tea insect pests classification based on artificial neural networks

Reference 18

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Observation f4267baa-256d-473c-a9c5-d9c1a1aa2d51 · outbound

This paper cites Crop pest detection by three-scale convolutional neural network with attention.

Crop Pest Classification Using Deep Learning Techniques: A Review Crop pest detection by three-scale convolutional neural network with attention

Reference 19

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This paper cites An effective pyramid neural network based on graph-related attentions structure for fine-grained disease and pest identification in intelligent agriculture.

Crop Pest Classification Using Deep Learning Techniques: A Review An effective pyramid neural network based on graph-related attentions structure for fine-grained disease and pest identification in intelligent agriculture

Reference 20

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Observation 20aae7c2-ac96-47cc-a465-d21d6aae3250 · outbound

This paper cites Attention Embedding ResNet for Pest Classification.

Crop Pest Classification Using Deep Learning Techniques: A Review Attention Embedding ResNet for Pest Classification

Reference 21

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Observation b0510a24-5dc7-487c-ad44-48f2bc6f9b5c · outbound

This paper cites Plant disease and insect pest identification based on vision transformer.

Crop Pest Classification Using Deep Learning Techniques: A Review Plant disease and insect pest identification based on vision transformer

Reference 22

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Observation bbbe88c3-6bc1-4c3f-9634-ae50e3ddafbf · outbound

This paper cites GA-GhostNet: A Lightweight CNN Model for Identifying Pests and Diseases Using a Gated Multi-Scale Coordinate Attention Mechanism.

Crop Pest Classification Using Deep Learning Techniques: A Review GA-GhostNet: A Lightweight CNN Model for Identifying Pests and Diseases Using a Gated Multi-Scale Coordinate Attention Mechanism

Reference 23

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Observation 0704f3c9-64aa-48c1-9f32-28e7f0d77b2a · outbound

This paper cites Self-supervised learning improves classification of agriculturally important insect pests in plants.

Crop Pest Classification Using Deep Learning Techniques: A Review Self-supervised learning improves classification of agriculturally important insect pests in plants

Reference 24

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This paper cites Detection of rice pests based on self-attention mechanism and multi-scale feature fusion.

Crop Pest Classification Using Deep Learning Techniques: A Review Detection of rice pests based on self-attention mechanism and multi-scale feature fusion

Reference 25

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Observation 5005d6f0-e3ff-435e-8371-4032ddc2d2f5 · outbound

This paper cites Using a hybrid convolutional neural network with a transformer model for tomato leaf disease detection.

Crop Pest Classification Using Deep Learning Techniques: A Review Using a hybrid convolutional neural network with a transformer model for tomato leaf disease detection

Reference 26

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Observation 46cba960-c704-4760-870b-7ce37566d05e · outbound

This paper cites An Efficient Insect Pest Classification Using Multiple Convolutional Neural Network Based Models.

Crop Pest Classification Using Deep Learning Techniques: A Review An Efficient Insect Pest Classification Using Multiple Convolutional Neural Network Based Models

Reference 27

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This paper cites Classification Accuracy Improvement for Small-Size Citrus Pests and Diseases Using Bridge Connections in Deep Neural Networks.

Crop Pest Classification Using Deep Learning Techniques: A Review Classification Accuracy Improvement for Small-Size Citrus Pests and Diseases Using Bridge Connections in Deep Neural Networks

Reference 28

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This paper cites Red Palm Weevil Detection in Date Palm Using Temporal UA V Imagery.

Crop Pest Classification Using Deep Learning Techniques: A Review Red Palm Weevil Detection in Date Palm Using Temporal UA V Imagery

Reference 29

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Observation f7862eb3-a8ad-45e6-8499-db560f8eb054 · outbound

This paper cites Exploring Deep Ensemble Model for Insect and Pest Detection from Images.

Crop Pest Classification Using Deep Learning Techniques: A Review Exploring Deep Ensemble Model for Insect and Pest Detection from Images

Reference 30

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This paper cites In: Early detection of locust swarms using deep learning.

Crop Pest Classification Using Deep Learning Techniques: A Review In: Early detection of locust swarms using deep learning

Reference 31

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This paper cites Crop pest classification with a genetic algorithm-based weighted ensemble of deep convolutional neural networks.

Crop Pest Classification Using Deep Learning Techniques: A Review Crop pest classification with a genetic algorithm-based weighted ensemble of deep convolutional neural networks

Reference 32

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Observation 662aa36c-3b48-42fb-914d-3a377df8bfe1 · outbound

This paper cites EfficientNetV2 Model for Plant Disease Classification and Pest Recognition.

Crop Pest Classification Using Deep Learning Techniques: A Review EfficientNetV2 Model for Plant Disease Classification and Pest Recognition

Reference 33

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Observation 1af10867-438b-4cea-a78d-c1fe531e8da2 · outbound

This paper cites Automatic classification of parasitized fruit fly pupae from X-ray images by convolutional neural networks.

Crop Pest Classification Using Deep Learning Techniques: A Review Automatic classification of parasitized fruit fly pupae from X-ray images by convolutional neural networks

Reference 34

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Observation 2c51c48c-c4fb-444f-b1f6-65de490b39ff · outbound

This paper cites Crop pest image recognition based on the improved ViT method.

Crop Pest Classification Using Deep Learning Techniques: A Review Crop pest image recognition based on the improved ViT method

Reference 35

Resolution: verified exact; doi, observed 2026-08-06T20:54:38.917128Z

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Observation 1831c02d-51cb-4a22-b1db-e79d8bb147ce · outbound

This paper cites Detecting Tea Tree Pests in Complex Backgrounds Using a Hybrid Architecture Guided by Transformers and Multi-Scale Attention Mechanism.

Crop Pest Classification Using Deep Learning Techniques: A Review Detecting Tea Tree Pests in Complex Backgrounds Using a Hybrid Architecture Guided by Transformers and Multi-Scale Attention Mechanism

Reference 36

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:54:42.806412Z

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Observation c831119a-1234-4689-9e4f-ae3a112be299 · outbound

This paper cites Efficient agricultural pest classification using vision transformer with hybrid pooled multihead attention.

Crop Pest Classification Using Deep Learning Techniques: A Review Efficient agricultural pest classification using vision transformer with hybrid pooled multihead attention

Reference 37

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Observation eaa28e95-72d1-45e0-bca2-9e050262d2e0 · outbound

This paper cites A New Hybrid ConvViT Model for Dangerous Farm Insect Detection.

Crop Pest Classification Using Deep Learning Techniques: A Review A New Hybrid ConvViT Model for Dangerous Farm Insect Detection

Reference 38

Resolution: verified exact; doi, observed 2026-08-06T20:54:38.513187Z

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Observation 3aa10f6f-6b67-4030-bd93-dc689f4fcddf · outbound

This paper cites YOLOv5-Based Rice Disease and Pest Recognition Design.

Crop Pest Classification Using Deep Learning Techniques: A Review YOLOv5-Based Rice Disease and Pest Recognition Design

Reference 40

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:54:41.841524Z

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Observation 21f611e1-d020-4856-b4dd-06f8dc19ba6d · outbound

This paper cites Improving long-tailed pest classification using diffusion model-based data augmentation.

Crop Pest Classification Using Deep Learning Techniques: A Review Improving long-tailed pest classification using diffusion model-based data augmentation

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Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:54:42.232749Z

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Observation 4e926ed6-5086-4ab4-bbc7-c45f0c96cdbe · outbound

This paper cites GAN-based semi-automated augmentation online tool for agricultural pest detection: A case study on whiteflies.

Crop Pest Classification Using Deep Learning Techniques: A Review GAN-based semi-automated augmentation online tool for agricultural pest detection: A case study on whiteflies

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Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:54:41.561458Z

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Observation 360e0097-01f2-4623-bf31-4187095d6655 · outbound

This paper cites Pest Identification and Control using Deep Learning and Augmented Reality.

Crop Pest Classification Using Deep Learning Techniques: A Review Pest Identification and Control using Deep Learning and Augmented Reality

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:54:45.375318Z

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Observation d80715da-eae1-4ed5-9437-b6b7286576d8 · outbound

This paper cites Field Crop Insect Recognition Based on Multiple Feature Fusion.

Crop Pest Classification Using Deep Learning Techniques: A Review Field Crop Insect Recognition Based on Multiple Feature Fusion

Reference 44

Resolution: verified exact; doi, observed 2026-08-06T20:54:38.018246Z

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Observation 52d5cd54-05ba-4995-88b7-dfb114acafb6 · outbound

This paper cites Deep learning-based identification of insect species for field crop pest management.

Crop Pest Classification Using Deep Learning Techniques: A Review Deep learning-based identification of insect species for field crop pest management

Reference 45

Resolution: verified exact; doi, observed 2026-08-06T20:54:37.606227Z

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Observation 09e86ad4-2457-4a5c-9dd2-3bd7b17fc060 · outbound

This paper cites An open access repository of images on plant health to enable the development of mobile disease diagnostics.

Crop Pest Classification Using Deep Learning Techniques: A Review An open access repository of images on plant health to enable the development of mobile disease diagnostics

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:54:45.142088Z

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Observation 0bdc8787-b5ce-4a37-b507-23f3bc82f5e5 · outbound

This paper cites Rice insect pest recognition and classification using an SVM-based expert system.

Crop Pest Classification Using Deep Learning Techniques: A Review Rice insect pest recognition and classification using an SVM-based expert system

Reference 47

Resolution: verified exact; doi, observed 2026-08-06T20:54:37.250593Z

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Observation 86b43506-8dd2-430e-9296-6d0883e8fd8a · outbound

This paper cites Paddy Doctor: Paddy Pest & Disease Dataset; 2022.

Crop Pest Classification Using Deep Learning Techniques: A Review Paddy Doctor: Paddy Pest & Disease Dataset; 2022

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:54:44.961844Z

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Observation 97b7a289-dd60-4051-b8c7-03a753141604 · outbound

This paper cites AgriPest: A Large-Scale Domain-Specific Benchmark Dataset for Practical Agricultural Pest Detection in the Wild.

Crop Pest Classification Using Deep Learning Techniques: A Review AgriPest: A Large-Scale Domain-Specific Benchmark Dataset for Practical Agricultural Pest Detection in the Wild

Reference 49

Resolution: verified exact; doi, observed 2026-08-06T20:54:37.102735Z

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Observation cd8a9a20-7204-4ae6-83b3-eafe71397791 · outbound

This paper cites A Deep-Learning-Based Detection Method for Small Target Tomato Pests in Insect Traps.

Crop Pest Classification Using Deep Learning Techniques: A Review A Deep-Learning-Based Detection Method for Small Target Tomato Pests in Insect Traps

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Resolution: verified exact; doi, observed 2026-08-06T20:54:36.941284Z

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Observation 7b83e3b8-f8ef-4aaf-aed4-fd2aed3c5181 · outbound

This paper cites A model for detecting tiny and very tiny pests in cotton fields based on super-resolution reconstruction.

Crop Pest Classification Using Deep Learning Techniques: A Review A model for detecting tiny and very tiny pests in cotton fields based on super-resolution reconstruction

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Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:54:41.215396Z

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Observation 5aadc26b-7afe-4d8f-ad9a-740507a8c1c7 · outbound

This paper cites A Lightweight YOLOv3-Based Detector for Real-Time Pest Detection on Edge Devices.

Crop Pest Classification Using Deep Learning Techniques: A Review A Lightweight YOLOv3-Based Detector for Real-Time Pest Detection on Edge Devices

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T20:54:36.449873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71e089c4-13cd-4561-9f9d-120f56f2d042 · outbound

This paper cites Lightweight YOLOv8 Model for Pest Detection with Low Power Consumption.

Crop Pest Classification Using Deep Learning Techniques: A Review Lightweight YOLOv8 Model for Pest Detection with Low Power Consumption

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:54:44.762430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8ce1747c-e99f-4d87-afa8-43db617e3c17 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Crop Pest Classification Using Deep Learning Techniques: A Review Distilling the Knowledge in a Neural Network

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T20:54:36.628532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aafbf2f2-4cbe-482a-86f3-e3f8dd5bd5a5 · outbound

This paper cites Continual lifelong learning with neural networks: A review.

Crop Pest Classification Using Deep Learning Techniques: A Review Continual lifelong learning with neural networks: A review

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T20:54:36.709698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62503a61-80e3-4576-a98d-ae40128f1aa4 · outbound

This paper cites Few-shot cross-domain adaptation for plant disease identification.

Crop Pest Classification Using Deep Learning Techniques: A Review Few-shot cross-domain adaptation for plant disease identification

Reference 56

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:54:40.837960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Reference resolution

Outbound references

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