Machine Learning for Developers

11.

Computer Vision for Developers

11.1.

Image Processing Fundamentals

11.1.1.

Image Representation

11.1.1.1.

11.1.1.2.

11.1.1.3.

11.1.2.

Image Preprocessing

11.1.2.1.

Resizing and Cropping

11.1.2.2.

11.1.2.3.

Data Augmentation

11.2.

Convolutional Neural Networks

11.2.1.

CNN Architecture

11.2.1.1.

Convolutional Layers

11.2.1.2.

11.2.1.3.

Fully Connected Layers

11.2.2.

Advanced CNN Concepts

11.2.2.1.

Batch Normalization

11.2.2.2.

Dropout Regularization

11.2.2.3.

Skip Connections

11.2.3.

Popular CNN Architectures

11.2.3.1.

11.2.3.2.

11.2.3.3.

11.2.3.4.

11.2.3.5.

11.3.

Computer Vision Tasks

11.3.1.

Image Classification

11.3.1.1.

Single-Label Classification

11.3.1.2.

Multi-Label Classification

11.3.1.3.

Fine-Grained Classification

11.3.2.

Object Detection

11.3.2.1.

Bounding Box Detection

11.3.2.2.

11.3.2.3.

11.3.3.

Image Segmentation

11.3.3.1.

Semantic Segmentation

11.3.3.2.

Instance Segmentation

11.3.3.3.

Panoptic Segmentation

11.3.4.

Image Generation

11.3.4.1.

Generative Adversarial Networks

11.3.4.2.

Variational Autoencoders

11.3.4.3.

Diffusion Models

11.4.

Transfer Learning in Computer Vision

11.4.1.

Pre-trained Model Selection

11.4.2.

Feature Extraction

11.4.3.

Fine-Tuning Strategies

11.4.4.

Domain Adaptation

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