Image Data Annotator for Smart Waste Classification
ImageClassification
I implemented a CNN-based waste classifier by training the model on over 4,000 images for automated recycling. My responsibilities focused on preparing, annotating, and labeling image data to train and evaluate the deep learning model. The project demanded careful image preprocessing, data augmentation, and iterative validation to ensure 92% classification accuracy.
• Labeled thousands of waste-category images by type (plastic, metal, organic, etc.)
• Used Python-based annotation techniques and OpenCV for image preparation
• Conducted regular QA on labels to minimize misclassification in outputs
• Integrated labeled datasets to fine-tune and retrain the classification model
I implemented a CNN-based waste classifier by training the model on over 4,000 images for automated recycling. My responsibilities focused on preparing, annotating, and labeling image data to train and evaluate the deep learning model. The project demanded careful image preprocessing, data augmentation, and iterative validation to ensure 92% classification accuracy. • Labeled thousands of waste-category images by type (plastic, metal, organic, etc.) • Used Python-based annotation techniques and OpenCV for image preparation • Conducted regular QA on labels to minimize misclassification in outputs • Integrated labeled datasets to fine-tune and retrain the classification model
2023 - 2023