This article explains the different evaluation metrics for deep learning object detection techniques. These include Average Precision (AP), Intersection over Union (IoU), and mean Average Precision (mAP) ...
Evaluation Metrics for Object Detection

Computer Vision in AI encompasses various tasks including classical computer vision, deep learning based image classification, image classification, object detection etc.
This article explains the different evaluation metrics for deep learning object detection techniques. These include Average Precision (AP), Intersection over Union (IoU), and mean Average Precision (mAP) ...
Many beginners in the field of computer vision and deep learning start with image classification. After exploring much deep learning image classification techniques, datasets, and architectures, they want to try something more exciting and challenging. And most of them move towards deep learning for object detection. But soon they realise that there are numerous techniques […] ...
In this tutorial, we will be implementing the Deep Convolutional Generative Adversarial Network architecture (DCGAN). We will go through the paper Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks first. This paper by Alec Radford, Luke Metz, and Soumith Chintala was released in 2016 and has become the baseline for many Convolutional GAN architectures […] ...
In this blog post, we train a Vanilla GAN using PyTorch to generate images from the MNIST digit dataset. ...
This blog post explores how to save model properly in PyTorch that helps in resuming training later on. ...
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