Model Evaluation Jobs

Here’s a Freelancer project post focused on the bird-versus-drone problem: **Title: Improve Image-Only Drone Detection to Reduce Bird False Positives on Raspberry Pi + Hailo-10H** I have an existing Raspberry Pi camera pipeline running a single-class (“Drone”) YOLO model on a Hailo-10H. Birds, especially at a distance, may be detected as drones. I need a computer-vision engineer to develop and evaluate an image-only solution that reduces these false positives without losing too many real drone detections. The camera is fixed to the drone body. The current model is available as a compiled HEF; availability of its original training weights and dataset needs to be confirmed. Development must go in a new `DetectionV2` folder. Existing Detection, camera, telemetry, and inte...

I need to fine-tune an existing computer-vision model for object detection so it performs reliably on my custom dataset. The base architecture is already selected; the task now is to prepare the data, set up transfer-learning, run hyper-parameter sweeps, and deliver a set of weights that reach an agreed-upon mAP on a held-out validation split. You may use PyTorch, TensorFlow, or another mainstream framework as long as the final model can be exported to ONNX. Please share examples of past work where you have successfully fine-tuned or trained object-detection networks—links to repos, papers, or short demos are ideal. Once we decide on the starting checkpoint and training environment, I’ll supply labeled images, class definitions, and any additional annotations you need. Delive...