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Computer Science
Computer Vision
Computer Vision with OpenCV
1. Introduction to OpenCV
2. Core Operations and Data Structures
3. Image Processing Fundamentals
4. Histograms and Image Analysis
5. Feature Detection and Description
6. Object Detection and Recognition
7. Video Analysis and Object Tracking
8. Advanced Image Processing
9. Camera Calibration and 3D Vision
10. Deep Learning Integration
Deep Learning Integration
DNN Module Overview
Supported Frameworks
Caffe
TensorFlow
PyTorch
Darknet
ONNX
Model Loading Process
Inference Pipeline
Image Classification
Pre-trained Models
Input Preprocessing
Image Resizing
Normalization
Mean Subtraction
Forward Pass Execution
Output Interpretation
Top-K Predictions
Object Detection Networks
Single Shot MultiBox Detector
SSD Architecture
Anchor Box Concepts
Multi-scale Detection
YOLO Family
YOLOv3 Implementation
YOLOv4 Implementation
YOLOv5 Integration
Detection Pipeline
Blob Creation
Network Inference
Post-processing
Non-Maximum Suppression
Semantic Segmentation
Segmentation Models
Pixel-wise Classification
Mask Generation
Visualization Techniques
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9. Camera Calibration and 3D Vision
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1. Introduction to OpenCV