Mean Average Precision (mAP) is a performance metric used for evaluating machine learning models. It is the most popular metric that is used by benchmark challenges such as PASCAL VOC, COCO, ImageNET ...
YOLOv4 and Darknet For Pothole Detection
In this blog post, we will be training YOLOv4 object detection model on a pothole detection dataset using the Darknet framework. Before we move further, let’s have an overview of the models that ...
Demystifying GPU Architectures For Deep Learning: Part 2
IntroductionAI specific features in recent NVIDIA GPUs2.1 Pascal microarchitecture (2016)2.2 Volta microarchitecture (2018)2.3 Turing microarchitecture (Late 2018)2.4 Ampere microarchitecture ...
Demystifying GPU Architectures For Deep Learning – Part 1
IntroductionCUDA programming model2.1 What is CUDA?2.2 Introduction to some important CUDA conceptsImplementing a dense layer in CUDASummary 1. Introduction A few months ago, we covered the ...
TensorFlow Model Optimization Toolkit – A Deep Dive
In the previous posts of the TFLite series, we introduced TFLite and the process of creating a model. In this post, we will take a deeper dive into the TensorFlow Model Optimization. We will explore ...
TensorFlow Lite Model Maker: Create Models for On-Device Machine Learning
In this article, we will learn how to create a TensorFlow Lite model using the TF Lite Model Maker Library. We will fine-tune a pre-trained image classification model on the custom dataset, further ...
