Deep Learning for Computer Vision

  1. Practical Implementation and Deployment
    1. Deep Learning Frameworks
      1. TensorFlow
        1. Keras High-level API
          1. TensorFlow Core
            1. TensorFlow Serving
            2. PyTorch
              1. Dynamic Computation Graphs
                1. Autograd System
                  1. TorchVision
                  2. Framework Comparison
                    1. Ease of Use
                      1. Performance
                        1. Community Support
                      2. Model Development Workflow
                        1. Experiment Design
                          1. Hypothesis Formation
                            1. Baseline Establishment
                            2. Code Organization
                              1. Modular Design
                                1. Configuration Management
                                  1. Version Control
                                  2. Debugging Techniques
                                    1. Gradient Checking
                                      1. Activation Visualization
                                        1. Loss Curve Analysis
                                        2. Hyperparameter Tuning
                                          1. Grid Search
                                            1. Random Search
                                              1. Bayesian Optimization
                                                1. Population-based Training
                                              2. Model Optimization
                                                1. Quantization
                                                  1. Post-training Quantization
                                                    1. Quantization-aware Training
                                                      1. INT8 Optimization
                                                        1. Dynamic Quantization
                                                        2. Pruning
                                                          1. Magnitude-based Pruning
                                                            1. Structured Pruning
                                                              1. Gradual Pruning
                                                                1. Lottery Ticket Hypothesis
                                                                2. Knowledge Distillation
                                                                  1. Teacher-Student Framework
                                                                    1. Soft Targets
                                                                      1. Feature Distillation
                                                                        1. Online Distillation
                                                                        2. Neural Architecture Search
                                                                          1. Automated Optimization
                                                                        3. Hardware Considerations
                                                                          1. Computing Platforms
                                                                            1. CPUs
                                                                              1. Multi-core Processing
                                                                                1. SIMD Instructions
                                                                                2. GPUs
                                                                                  1. Parallel Processing
                                                                                    1. Memory Hierarchy
                                                                                      1. CUDA Programming
                                                                                      2. TPUs
                                                                                        1. Tensor Processing Units
                                                                                          1. Specialized Hardware
                                                                                          2. FPGAs
                                                                                            1. Reconfigurable Computing
                                                                                          3. Memory Management
                                                                                            1. GPU Memory
                                                                                              1. Batch Size Optimization
                                                                                                1. Gradient Accumulation
                                                                                                2. Distributed Training
                                                                                                  1. Data Parallelism
                                                                                                    1. Model Parallelism
                                                                                                      1. Synchronous vs Asynchronous
                                                                                                    2. Edge Deployment
                                                                                                      1. Mobile Optimization
                                                                                                        1. Model Compression
                                                                                                          1. Efficient Architectures
                                                                                                            1. On-device Inference
                                                                                                            2. Deployment Frameworks
                                                                                                              1. TensorFlow Lite
                                                                                                                1. Model Conversion
                                                                                                                  1. Optimization Tools
                                                                                                                  2. Core ML
                                                                                                                    1. iOS Integration
                                                                                                                    2. ONNX Runtime
                                                                                                                      1. Cross-platform Deployment
                                                                                                                      2. OpenVINO
                                                                                                                        1. Intel Hardware Optimization
                                                                                                                      3. Real-time Constraints
                                                                                                                        1. Latency Requirements
                                                                                                                          1. Power Consumption
                                                                                                                            1. Memory Limitations
                                                                                                                          2. Model Interpretability
                                                                                                                            1. Visualization Techniques
                                                                                                                              1. Filter Visualization
                                                                                                                                1. Feature Map Analysis
                                                                                                                                  1. Activation Maximization
                                                                                                                                  2. Attribution Methods
                                                                                                                                    1. Gradient-based Attribution
                                                                                                                                      1. Integrated Gradients
                                                                                                                                        1. SHAP Values
                                                                                                                                        2. Attention Visualization
                                                                                                                                          1. Attention Maps
                                                                                                                                            1. Class Activation Maps
                                                                                                                                              1. Grad-CAM
                                                                                                                                                1. Grad-CAM++
                                                                                                                                                2. Adversarial Analysis
                                                                                                                                                  1. Adversarial Examples
                                                                                                                                                    1. Robustness Testing
                                                                                                                                                      1. Failure Case Analysis
                                                                                                                                                      2. Model Debugging
                                                                                                                                                        1. Error Analysis
                                                                                                                                                          1. Bias Detection
                                                                                                                                                            1. Fairness Assessment

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                                                                                                                                                        7. Advanced Topics and Applications

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                                                                                                                                                        1. Foundations of Computer Vision and Deep Learning