🎓 Course [UDEMY] Object Detection And Tracking Using Yolov11 : Deep Learning

Object Detection And Tracking Using Yolov11 : Deep Learning

Description​

Object Detection and Tracking Using YOLOv11 Master the art of real-time object detection and tracking with YOLOv11 ! This course will guide you through the fundamentals of YOLO (You Only Look Once) and help you develop a robust system capable of detecting and tracking multiple objects in images and videos. Whether you're a beginner or an experienced AI enthusiast, this course will provide hands-on experience in training and deploying YOLOv11 models for real-world applications.
COURSE HIGHLIGHTS:
Understand YOLOv11’s architecture and its advantages in object detection tasks.
Learn how to collect, label, and preprocess data for training YOLOv11.
T rain YOLOv11 models to detect and track object , fine-tuning parameters for accuracy.
Implement your trained model for real-time object detection and tracking in video feeds or IoT setups.
Analyze detection results, identify challenges, and refine your model for better performance.
This course is perfect for developers, AI enthusiasts, and anyone in the agriculture or livestock industry looking to integrate AI solutions into their workflows. By the end of the course, you’ll have built a fully functional object detection and tracking system and gained valuable machine learning expertise. Get ready to dive into hands-on projects, powerful AI techniques, and practical applications. Let’s start building intelligent computer vision systems together!
  • Understand YOLOv11’s architecture and its advantages in object detection tasks.
  • Learn how to collect, label, and preprocess data for training YOLOv11.
  • T rain YOLOv11 models to detect and track object , fine-tuning parameters for accuracy.
  • Implement your trained model for real-time object detection and tracking in video feeds or IoT setups.
  • Analyze detection results, identify challenges, and refine your model for better performance.

Who this course is for:​

  • Computer Science Student
  • YOLO developers
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