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You will get Outdoor object detection for animal monitoring on a farm


Project details
This project implements an object detection model using Tensor Flow to monitor and track animal movements. The system is designed to automatically detect, analyze, and alert users about any animal activity, providing real-time monitoring and enhancing surveillance capabilities.
AI Development Type
Deep Learning, Model Tuning, Software MaintenanceAI Tools
OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$100
|
Standard
$150
|
Advanced
$200
|
|---|---|---|---|
| Delivery Time | 1 day | 1 day | 1 day |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | |||
Model Documentation | - | ||
Ontology | - | - | |
Source Code | - | - | |
Taxonomy | - | - |
Frequently asked questions
About Pradeeba
Data Science| AI&ML| Deep Learning| Computer Vision| LLMs
Chennai, India - 10:08 am local time
I’m proficient in object classification using YOLO models. I have hands-on experience with all major YOLO versions, including YOLOv1, YOLOv5, YOLOv7, YOLOv8 and YOLO11.
I’ve worked with PoseNet, and MoveNet for action recognition.
My computer vision work involves OpenCV, SLAM, TensorFlow, PyTorch, ONNX, CUDA, TensorRT, OpenVINO, and NPUs. I use Albumentations for image augmentation, DeepSORT and SORT for object tracking, and perform image preprocessing and camera calibration for robotics and embedded systems.
Steps for completing your project
After purchasing the project, send requirements so Pradeeba can start the project.
Delivery time starts when Pradeeba receives requirements from you.
Pradeeba works on your project following the steps below.
Revisions may occur after the delivery date.
Project Initiation
Discuss project scope, technical specifications, and expected outcomes.
Data Collection & Model Training
Train the object detection model using TensorFlow (YOLO, Faster R-CNN, or SSD).