Underfitting — Overfitting, Vanishing — Exploding Gradient Problems and their possible solutions with experiment results and scratch codes

A comprehensive guide to convolution and convolutional neural networks for image classification, from implementation with Python and TensorFlow to optimization and transfer learning techniques

Image by Author

A quick intro for Neural Networks, Unsupervised and Supervised Learning, the difference between Regression and Classification and their simple modeling with neural networks, example implementation from scratch with Python

  • Neural Network Fundamentals
  1. General Structure of a Neural Network
  2. Unsupervised Learning
  3. Supervised Learning
  4. Deep Neural Networks
  5. Activation Function Types and Optimization Techniques

Epipolar Geometry basics like Essential Matrix, Fundamental Matrix, Triangulation, Feature Matching are explained with their MATLAB code implementations

A user interface implemented with QT Creator, Opencv, and C++ to make the user able for realizing what they learned during this tutorial like Camera Calibration, Fundamental-Essential Matrix Estimation, Triangulation

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A series about Visual Perception Fundamentals like Camera Calibration, Epipolar Geometry, and their mathematical implementations from scratch

A brief explanation of these 3 terms that form the basis of relation— similarity analysis for different subjects like Region Growing, an algorithm used in Image Segmentation

Pixel p and its 4-neighborhood “Image by Author”

Classical Computer Vision-Based Image Segmentation methods like Thresholding, Region-Based, Edge Detection Based and Morphological Segmentation are explained in 1 post to make a quick start with this domain

  • Classical Computer Vision-Based Approaches
  1. Thresholding
  2. Region-Based Methods

Yağmur Çiğdem Aktaş

www.linkedin.com/in/yağmur-cigdem-aktas aktas.yagmur@gmail.com https://github.com/YCAyca You can reach all the codes used in my posts from this github link!

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