mart mobile application to recognize tomato leaf diseases using Convolutional Neural Networks
원문 초록
The automatic identification and diagnosis of tomato leaves diseases are highly desired in field of agriculture information. Recently Deep Convolutional Neural networks (CNN) has made tremendous advances in many fields, close to computer vision such as classification, object detection, segmentation, achieving better accuracy than human-level perception. In spite of its tremendous advances in computer vision tasks, CNN face many challenges, such as computational burden and energy, to be used in mobile phone and embedded systems. In this study, we propose an efficient smart mobile application model based on deep CNN to recognize tomato leaf diseases. To build such application, our model has been inspired from MobileNet CNN model and can recognize the 10 most common types of Tomato leaf disease. Trained on tomato leafs dataset, to build our application 7176 images of tomato leaves are used in the smart mobile system, to perform a Tomato disease diagnostics.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Structured Pruning and Quantization for Learned Image Compression
OD3: Optimization-free Dataset Distillation for Object Detection
Unfolding the Past: A Comprehensive Deep Learning Approach to Analyzing Incunabula Pages
A Robust Feature Downsampling Module for Remote Sensing Visual Tasks
Automatic Detection and Image Recognition of Precision Agriculture for Citrus Diseases
R-MnasNet: Reduced MnasNet for Computer Vision
토론
이 논문과 연결된 포럼 글이 아직 없습니다.