Posts Written by Petru Potrimba

In this guide, we discuss what DETR is, how it works, the strengths and disadvantages of DETR, and how DETR performs.

In this guide, you will learn what R-CNN is, how it works, the advantages and disadvantages of the R-CNN architecture, and how R-CNN performs.

In this guide, we discuss what OneFormer is, how it works, and the performance of OneFormer benchmarked against three datasets.

This guide explores what hyperparameter tuning is, common hyperparameters in computer vision, methods of tuning hyperparameters, and more.

In this guide, we discuss what Detic is, how it works, notable characteristics of Detic, and the limitations associated with the model.

In this guide, we discuss what dataset distillation is, the methods through which a dataset can be distilled, and the applications of distilled datasets in computer vision.

In this guide, we discuss what knowledge distillation is, how it works, why knowledge distillation is useful, and the different methods of distilling knowledge from one model to another.

In this guide, we discuss what a Convolutional Neural Network (CNN) is, how they work, and discuss various different applications of CNNs in computer vision models.

In this guide, we explore what Transformers are, why Transformers are so important in computer vision, and how they work.

In this article, we discuss what a neural network is and walk through the most common network architectures.

In this article, we discuss what an activation function is, why they are used, and what types of activation functions are commonly used.

In this article, we discuss what zero-shot learning is, how it works, and when zero-shot learning is and is not useful.

In this post, we discuss what semi-supervised learning is and walk through the techniques used in semi-supervised learning.

Suppose you have a problem you want to solve with computer vision but few images on which you can base your new model. What can you do? You could wait