YOLO Jobs

this project is to develop an infrared small target detection system using classical image processing techniques. The system will analyse infrared images and detect very small targets that are often hidden in complex background environments such as sky, sea, and land scenes. The project focuses on combining local contrast-based methods and nonlocal spatial information techniques to improve detection accuracy while maintaining computational efficiency. The project will use a public benchmark dataset: Dataset: NUAA-SIRST Dataset Source: GitHub open-access repository Dataset Link: Step 1 – Data Preparation Step 2 – Image Preprocessing Step 3 – Local Target Enhancement Implement the Dual Window Local Contrast Method (DW-LCM). Step 4 – Nonlocal Background Suppressi...

I need a small software tool that runs on an NVIDIA Jetson Orin Nano to capture, organize, and export a labeled image/video dataset for training YOLO object detection models. The camera is an 640×512 sensor connected via MIPI CSI-2 (4 lanes) using a 22-pin ribbon cable to the Jetson Orin Nano CSI connector. The tool should support live preview, capture, dataset management, and YOLO-format export. Build an application that: - Interfaces with the camera on Jetson Orin Nano - Acquire frames from the MIPI CSI-2 camera reliably (GStreamer / V4L2 / libargus or best approach for this sensor). - Provide live preview (grayscale or false color optional). - Display FPS + resolution. Dataset capture: - Capture single frames and/or short clips (optional). - Save images in a consist...

I need a compact, fast object-detection model that runs directly on an edge board (Jetson Nano, Raspberry Pi, Coral or similar) and processes aerial images from drones. The immediate application is surveillance, yet the solution should stay flexible enough to be reused later in agriculture or disaster-response scenarios. Source imagery will contain a mix of people, cars, buses, bicycles and assorted infrastructure. The model must be especially reliable at spotting people and critical infrastructure elements, while still recognising the wider vehicle classes.I am open to any justified architecture (YOLOv8, MobileNet-SSD, EfficientDet-Lite, or superior alternatives)—provided it outperforms YOLOv9c and similar models while delivering real-time inference on edge devices once quantized o...