U-Net Architecture For Image Segmentation
Image segmentation makes it easier to work with computer vision applications. We look at U-Net, a convolutional neural network.
Object Detection Using Mask R-CNN with TensorFlow 1.14 and Keras (TENSORFLOW-1-X)
URL: https://www.progressiverobot.com/mask-r-cnn-in-tensorflow-1-x/ > Editors note: This article was originally released in November of 2020, and some of it's information is outdated. The core theory shown is nonetheless backed up by solid research, however, and the code is still executable. Mask R-CNN is an object detection model based on deep convolutional neural networks (CNN) developed by […]
Writing AlexNet from Scratch in PyTorch
Learn how to build the AlexNet architecture from scratch using PyTorch. This step-by-step guide covers each layer in detail, helping you understand and implement this classic convolutional neural network.
Depth Anything V2: A Powerful, Monocular Depth Estimation Model
This article explores Depth Anything V2, a robust solution for monocular depth estimation designed to handle any image under any conditions. This approach aims to create a simple yet powerful foundation model for depth estimation.
Face Generation with GANs
A primer for developing a custom neural network to learn to generate novel facial images using Deep Convolutional generative adversarial networks.
Introduction to DETR – Part 1
DETR introduces a completely new architecture, setting a new standard in the object detection field. In this article, we explore the Detection Transformer (DETR) concept, highlighting its groundbreaking approach and the significant advancements it brings to object detection technology.
Automatic Hyperparameter Optimization With Keras Tuner
Learn how to utilize the search algorithms of Keras Tuner to automatically get the best hyperparameters for Tensorflow models.
What’s New in YOLOv11-Finetune on Custom Dataset using GPU Droplets
In this tutorial we will demonstrate how to finetune YOLOv11, and how to use the cloud provider’s GPU Droplets to train the model for your specific data needs. This guide will help you with all the necessary steps require to fine-tune the model using custom dataset.
NVIDIA Sana – A Foundation Image Generation Model at Lightning Speeds
Discover NVIDIA Sana, the groundbreaking image generation model offering unparalleled speed and precision. Learn how to deploy and run Sana effortlessly on GPU cloud servers with step-by-step guides and comparisons to FLUX and Stable Diffusion.
Introduction to DETR – Part 2: The Crucial Role of the Hungarian Algorithm
In part 2 of this tutorial series, we look at DETR’s Hungarian Algorithm in depth to show how it minimizes cost.