Personal Project
PlantVision AI
PlantVision AI: Deep Learning Model for Plant Species Classification
2023New YorkPersonal Research Project
Developed a high-accuracy deep learning model using PyTorch for plant species classification, training on a dataset of over 40,000 plant images across 25 different species, achieving 95% accuracy in identification.
Technologies & Skills
PyTorch
Deep Learning
Computer Vision
Python
Neural Networks
Data Processing
Transfer Learning
GPU Computing
Project Objectives
- Create a highly accurate plant species classification model
- Process and prepare large-scale image dataset
- Implement efficient training pipeline using GPU acceleration
- Optimize model architecture for maximum accuracy
Key Achievements
- Built and trained a custom CNN architecture using PyTorch
- Processed and augmented dataset of 40,000+ plant images
- Achieved 95% accuracy in species classification
- Implemented transfer learning techniques for improved model performance
- Developed data preprocessing pipeline for image standardization
- Created robust validation methodology for model testing
Project Outcomes
- Achieved 95% classification accuracy across 25 plant species
- Successfully processed and utilized 40,000+ training images
- Developed efficient data augmentation pipeline
- Created scalable solution for plant species identification
Team Composition
- Solo Project