Article

Application of knowledge distillation method with dynamic adjustment of temperature parameters in pest classification

2024-08-01

Abstract excerpt

<title>Abstract</title> <p>In recent years, the output of China's four major crops has declined due to pests and diseases. This situation poses a serious challenge to food security. Therefore, timely detection and prevention of diseases is essential. First, we use data enhancement techniques to augment the data to improve the generalization ability of the model. Secondly, to reduce the model parameters and facili...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 278514de-b949-5543-958d-997c78b0b542
DOI: 10.21203/rs.3.rs-4691672/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Application of knowledge distillation method with dynamic adjustment of temperature parameters in pest classificationDOI 10.21203/rs.3.rs-4691672/v1Read

An Efficient Dynamic Deep Learning Methodology for Identification of Plant Disease and it’s classificationSemantic proximity Read

Deep learning-based disease detection in peanut cultivars utilizing transfer learningSemantic proximity Read

Prediction of tomato leaf disease using deep learning approachSemantic proximity Read

Study on Accurate Grading Prediction Model of Tobacco Weather Fleck Based on Internet of ThingsSemantic proximity Read

Hybrid Explainable DeiT-Based Framework for Plant Disease Classification and Severity EstimationSemantic proximity Read

Cross-dataset evaluation of deep learning models for plant pest and disease diagnosisSemantic proximity Read

Deep Learning-Driven Plant Disease Detection and Custom Fertilizer FormulationSemantic proximity Read

YOLOv11-RCDWD: A New Efficient Model for Detecting Maize Leaf Diseases Based on the Improved YOLOv11Semantic proximity Read

Precision Agriculture using Machine Learning and Deep Learning Algorithms: A Comprehensive StudySemantic proximity Read

A Real-Time Common Rust Maize Leaf Disease Severity Identifications and Pesticide Dose Recommendation Using Deep Neural NetworkSemantic proximity Read

Intelligent Drone Assisted Plant Disease Detectionand Precision Pesticide Spraying Using a Residual-Inception Deep Learning FrameworkSemantic proximity Read

Precision Agriculture-Based Pest Detection Solutions Using AI Algorithms Simulated with Complex Logic Gates Integration and 3D BioprintingSemantic proximity Read