01Computer Vision2024
Evaluating Instance Segmentation for Waste Detection
A computer vision project comparing SOLOv2, Mask R-CNN and U-Net for waste segmentation on the TACO dataset, with a multi-axis evaluation framework — accuracy, deployment efficiency and compute cost — built to compare them fairly under resource-limited deployment constraints.
- 3
- Architectures compared — SOLOv2, Mask R-CNN, U-Net
- 3-axis
- Accuracy · efficiency · compute-cost evaluation
- PyTorch
- MMDetection
- SOLOv2
- Mask R-CNN
- U-Net
- TensorBoard
