CropDeep: The Crop Vision Dataset for Deep-Learning-Based Classification and Detection in Precision Agriculture
Explore this paper's citation graph
Summary
The CropDeep species classification and detection dataset, consisting of 31,147 images with over 49,000 annotated instances from 31 different classes, is presented and it is suggested that the YOLOv3 network has good potential application in agricultural detection tasks.
- Type
- article
- Published
- 2019-03-01
- Cited by
- 399
- References
- 43
- Access
- Open access
- OpenAlex
- https://openalex.org/W2915594101
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:73493006
Keywords
Deep learning, Artificial intelligence, Computer science, Machine learning, Benchmark (surveying)
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- Deliberation on Design Strategies of Automatic Harvesting Systems: A Survey
- Irrigation Water Quality for Leafy Crops: A Perspective of Risks and Potential Solutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- The Caltech-UCSD Birds-200-2011 Dataset
- The Pascal Visual Object Classes (VOC) Challenge
- Evaluation of output embeddings for fine-grained image classification
- Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case
- Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
- Internet of Things (IoT): A vision, architectural elements, and future directions
- ImageNet Large Scale Visual Recognition Challenge
- A Visual Vocabulary for Flower Classification
- ImageNet classification with deep convolutional neural networks
- First Pregnancies, Livebirth and In Vitro Fertilization Outcomes After Transplantation of Frozen-Banked Ovarian Tissue with a Human Extracellular Matrix Scaffold using Robot-Assisted Minimally Invasive Surgery
- Deep Residual Learning for Image Recognition
- Regulated deficit irrigation for crop production under drought stress. A review
- Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
- SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size
- Cataloging Public Objects Using Aerial and Street-Level Images — Urban Trees
- YOLO9000: Better, Faster, Stronger
Cited by
- A New Method of Mixed Gas Identification Based on a Convolutional Neural Network for Time Series Classification
- Deep Convolutional Neural Network for Mapping Smallholder Agriculture Using High Spatial Resolution Satellite Image
- Early warning of cyanobacteria blooms outbreak based on stoichiometric analysis and catastrophe theory model
- Meteorological sequence prediction based on multivariate space-time auto regression model and fractional calculus grey model
- Walking Gait Phase Detection Based on Acceleration Signals Using LSTM-DNN Algorithm
- A Novel Framework for Trash Classification Using Deep Transfer Learning
- Investigation of Optimal Network Architecture for Asparagus Spear Detection in Robotic Harvesting
- A Neuron-Based Kalman Filter with Nonlinear Autoregressive Model
- Walking Gait Phase Detection Based on Acceleration Signals Using Voting-Weighted Integrated Neural Network
- Nonlinear dynamic numerical analysis and prediction of complex system based on bivariate cycling time stochastic differential equation
- Deep Hybrid Model Based on EMD with Classification by Frequency Characteristics for Long-Term Air Quality Prediction
- Group Decision-Making Support for Sustainable Governance of Algal Bloom in Urban Lakes
- Deep Learning Predictor for Sustainable Precision Agriculture Based on Internet of Things System
- Harvestable Black Pepper Recognition Using Computer Vision
- Effective SAR image segmentation and classification of crop areas using MRG and CDNN techniques
- Hybrid Deep Learning Predictor for Smart Agriculture Sensing Based on Empirical Mode Decomposition and Gated Recurrent Unit Group Model
- A Biologically Interpretable Two-stage Deep Neural Network (BIT-DNN) For Hyperspectral Imagery Classification
- Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey
- Agricultural Robotics for Field Operations
- STATUS PREDICTION BY 3D FRACTAL NET CNN BASED ON REMOTE SENSING IMAGES
Related papers
- Theoretical Analysis of the Benchmark for Choosing Manipulative Instruments of Monetary Policies
- Study and application of telecom operators system security state baseline
- Analysis of the Baseline Decorrelation and Critical Baseline of Interferometric SAR
- Research of Baseline Implement
- A Study on the Role of Precision Agriculture in Agro-Industry
- Opinion paper: Precision agriculture, smart agriculture, or digital agriculture
- Precision agriculture in India - challenges and opportunities