Computer Vision & Edge AI Β· From training to inference, running models on real hardware
I work on the engineering side of computer vision β model development, inference optimization, and edge deployment. I believe a model's value is measured by how it performs on real hardware.
Vision Models Object detection, segmentation, OCR, face, ReID, fine-grained classification. YOLO family, CRNN/CTC, multimodal models β from paper to production.
Model Engineering ONNX, TensorRT, Triton. Pruning, distillation, quantization. CV workflow toolkits spanning data processing, model export, inference, and evaluation.
Edge Deployment NVIDIA Jetson, Huawei Ascend, SOPHON, Horizon, Rockchip RKNN. C++ multi-stream inference, model acceleration, cross-platform adaptation.