标题
Fine-Grained Image Classification for Crop Disease Based on Attention Mechanism
作者
关键词
-
出版物
Frontiers in Plant Science
Volume 11, Issue -, Pages -
出版商
Frontiers Media SA
发表日期
2020-12-22
DOI
10.3389/fpls.2020.600854
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Tell and guess: cooperative learning for natural image caption generation with hierarchical refined attention
- (2020) Wenqiao Zhang et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Grape Leaf Disease Identification Using Improved Deep Convolutional Neural Networks
- (2020) Bin Liu et al. Frontiers in Plant Science
- Comparison of convolution neural networks for smartphone image based real time classification of citrus leaf disease
- (2020) Utpal Barman et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Pedestrian object detection with fusion of visual attention mechanism and semantic computation
- (2019) Feng Xiao et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Analysis of transfer learning for deep neural network based plant classification models
- (2019) Aydin Kaya et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Three-Stream Attention-Aware Network for RGB-D Salient Object Detection
- (2019) Hao Chen et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Convolutional Neural Networks for the Automatic Identification of Plant Diseases
- (2019) Justine Boulent et al. Frontiers in Plant Science
- Multi-model LSTM-based convolutional neural networks for detection of apple diseases and pests
- (2019) Muammer Turkoglu et al. Journal of Ambient Intelligence and Humanized Computing
- Attention embedded residual CNN for disease detection in tomato leaves
- (2019) Karthik R. et al. APPLIED SOFT COMPUTING
- Image caption generation with dual attention mechanism
- (2019) Maofu Liu et al. INFORMATION PROCESSING & MANAGEMENT
- Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild
- (2018) Artzai Picon et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep learning models for plant disease detection and diagnosis
- (2018) Konstantinos P. Ferentinos COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A comparative study of fine-tuning deep learning models for plant disease identification
- (2018) Edna Chebet Too et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Object-Part Attention Model for Fine-Grained Image Classification
- (2018) Yuxin Peng et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- An intelligent mobile application for diagnosis of crop diseases in Pakistan using fuzzy inference system
- (2018) Muhammad Toseef et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Impact of dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification
- (2018) Jayme Garcia Arnal Barbedo COMPUTERS AND ELECTRONICS IN AGRICULTURE
- High-Performance Deep Neural Network-Based Tomato Plant Diseases and Pests Diagnosis System With Refinement Filter Bank
- (2018) Alvaro F. Fuentes et al. Frontiers in Plant Science
- Detection of grapevine yellows symptoms in Vitis vinifera L. with artificial intelligence
- (2018) Albert Cruz et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Identification of rice diseases using deep convolutional neural networks
- (2017) Yang Lu et al. NEUROCOMPUTING
- How Deep Learning Extracts and Learns Leaf Features for Plant Classification
- (2017) Sue Han Lee et al. PATTERN RECOGNITION
- Deep Learning for Image-Based Cassava Disease Detection
- (2017) Amanda Ramcharan et al. Frontiers in Plant Science
- Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach
- (2017) Miraemiliana Murat et al. PeerJ
- Detecting Densely Distributed Graph Patterns for Fine-Grained Image Categorization
- (2016) Luming Zhang et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Using Deep Learning for Image-Based Plant Disease Detection
- (2016) Sharada P. Mohanty et al. Frontiers in Plant Science
- Image-based phenotyping of plant disease symptoms
- (2015) Andrew M. Mutka et al. Frontiers in Plant Science
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started