Flower Recognition Using Convolutional Neural Network
Artificial intelligence is the new frontier in the history of technological development, opening the way to an absolutely new phase with qualitative changes in the most diverse industries. One of the game-changing technologies is Convolutional Neural Networks (CNNs), which have shown good results in various tasks related to image recognition. In this paper, the application of CNN in the domain of flower recognition, which has large implications for agriculture and marketing, is presented. The study demonstrates effective classification of flower species using deep learning techniques with potential applications in automated botanical identification and agricultural systems.
Flower Recognition Using Convolutional Neural Network
Artificial intelligence is the new frontier in the history of technological development, opening the way to an absolutely new phase with qualitative changes in the most diverse industries. One of the game-changing technologies is Convolutional Neural Networks (CNNs), which have shown good results in various tasks related to image recognition. In this paper, the application of CNN in the domain of flower recognition, which has large implications for agriculture and marketing, is presented. The study demonstrates effective classification of flower species using deep learning techniques with potential applications in automated botanical identification and agricultural systems.
Key Highlights
- Application of CNN in the domain of flower recognition with agricultural implications
- Effective classification of flower species using deep learning techniques
- Potential applications in automated botanical identification systems
- Game-changing technology with qualitative changes across diverse industries
Technologies Used
- Convolutional Neural Networks - Deep learning architecture for image processing
- Flower Recognition - Species identification and classification
- Image Classification - Computer vision pattern recognition
- Deep Learning - Neural network-based learning algorithms
- Computer Vision - Visual data processing and analysis
- Agricultural Applications - Technology for farming and agriculture
- Botanical Identification - Automated plant species recognition
Read the full research paper on ResearchGate!