Generative Adversarial Networks (GANs) are built upon a dynamic interaction between two neural networks: a generator and a discriminator. The…
ARTIFICIAL INTELLIGENCE (50) – Computer vision (5) – Autoencoder, Variational Autoencoders (VAEs) and Diffusion models
When training an autoencoder, the objective is for the model to reconstruct its own input. For this reason, the target…
ARTIFICIAL INTELLIGENCE (49) – Computer vision (4) Transfer Learning
The article explains the concept of Transfer Learning in machine learning. Instead of training a deep neural network from the…
ARTIFICIAL INTELLIGENCE (48) – Natural Language Processing (23) Regular Fine-Tuning and LoRA Fine-Tuning
Regular Fine‑Tuning In standard fine‑tuning: The model starts with pretrained weights W, during training, the model learns a full weight…
ARTIFICIAL INTELLIGENCE (47) – Computer vision (3) Semantic segmentation using a sliding window classifier and a CNN
This article explains a naive approach to semantic segmentation using a sliding window classifier and a CNN (Convolutional Neural Network).…
ARTIFICIAL INTELLIGENCE (46) – Computer Vision (2) Semantic segmentation
Semantic segmentation is a technique in computer vision where each pixel of an image is classified into a specific category.…
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