Welcome to our tutorial : Image animation brings life to the static face in the source image according to the driving video, using the Thin-Plate Spline Motion Model! In this tutorial, we’ll take you through the entire process, from setting up the required environment to running your very own animations. What You’ll Learn : Part […]
Transform Static Images into Lifelike Animations Read More »
In this tutorial, we build a vehicle classification model using VGG16 for feature extraction and XGBoost for classification! 🚗🚛🏍️ It will based on Tensorflow and Keras 🔍 What You’ll Learn 🔍: 🖼️ Part 1: We kick off by preparing our dataset, which consists of thousands of vehicle images across five categories. We demonstrate how to
Object Classification using XGBoost and VGG16 | Classify vehicles using Tensorflow Read More »
This tutorial provides a step-by-step easy guide on how to implement and train a CNN model for Malaria cell classification using TensorFlow and Keras. 🔍 What You’ll Learn 🔍: Data Preparation — In this part, you’ll download the dataset and prepare the data for training. This involves tasks like preparing the data , splitting into training
How to classify Malaria Cells using Convolutional neural network Read More »
This tutorial provides a step-by-step guide on how to implement and train a U-Net model for Melanoma detection using TensorFlow/Keras. 🔍 What You’ll Learn 🔍: Building U-net model : Learn how to construct the model using TensorFlow and Keras. Model Training: We’ll guide you through the training process, optimizing your model to generate masks in the
How to segment X-Ray lungs using U-Net and Tensorflow Read More »
This tutorial provides a step-by-step guide on how to implement and train a U-Net model for Melanoma detection using TensorFlow/Keras. 🔍 What You’ll Learn 🔍: Data Preparation: We’ll begin by showing you how to access and preprocess a substantial dataset of Melanoma images and corresponding masks. Data Augmentation: Discover the techniques to augment your dataset.
Medical Melanoma Detection | TensorFlow U-Net Tutorial using Unet Read More »
This tutorial provides a step-by-step guide on how to implement and train a U-Net model for animals segmentation using TensorFlow/Keras. The tutorial is divided into four parts: Part 1: Data Preprocessing and Preparation In this part, you load and preprocess the persons dataset, including resizing images and masks, converting masks to binary format, and splitting
Creating an Animal Segmentation Model with U-Net and TensorFlow Keras Read More »
This tutorial provides a step-by-step guide on how to implement and train a U-Net model for persons segmentation using TensorFlow/Keras. The tutorial is divided into four parts: Part 1: Data Preprocessing and Preparation In this part, you load and preprocess the persons dataset, including resizing images and masks, converting masks to binary format, and splitting
U-net Image Segmentation | How to segment persons in images Read More »
This tutorial provides a step-by-step guide on how to implement and train a U-Net model for polyp segmentation using TensorFlow/Keras. The tutorial is divided into four parts: 🔹 Data Preprocessing and Preparation In this part, you load and preprocess the polyp dataset, including resizing images and masks, converting masks to binary format, and splitting the
U-net Medical Segmentation with TensorFlow and Keras (Polyp segmentation) Read More »
👁️ CNN Image Classification for Retinal Health Diagnosis with TensorFlow and Keras! 👁️ How to gather and preprocess a dataset of over 80,000 retinal images, design a CNN deep learning model , and train it that can accurately distinguish between these health categories. What You’ll Learn: 🔹 Data Collection and Preprocessing: Discover how to acquire
Build a CNN Model for Retinal Image Diagnosis Read More »
📽️ In our latest video tutorial, we will create a dog breed recognition model using the NasLarge pre-trained model 🚀 and a massive dataset featuring over 10,000 images of 120 unique dog breeds 📸. What You’ll Learn: 🔹 Data Preparation: We’ll begin by downloading a dataset of of more than 20K Dogs images, neatly categorized
120 Dog Breeds, more than 10,000 Images: Deep Learning Tutorial for dogs classification Read More »
