Computer Vision

Computer Vision is the field that is dominated by Deep Learning. Face recognition, image classification, video prediction are only a tiny portion of applications

Convolutional Neural Networks · Medical · Computer Vision · Pytorch

An overview of Unet architectures for semantic segmentation and biomedical image segmentation

Learn everything about one of the most famous convolutional neural network architectures that is widely used on image segmentation.

Medical · Computer Vision

Introduction to medical image processing with Python: CT lung and vessel segmentation without labels

Find out the basics of CT imaging and segment lungs and vessels without labels with 3D medical image processing techniques.

Attention and Transformers · Computer Vision · Pytorch

How the Vision Transformer (ViT) works in 10 minutes: an image is worth 16x16 words

In this article you will learn how the vision transformer works for image classification problems. We distill all the important details you need to grasp along with reasons it can work very well given enough data for pretraining.

Convolutional Neural Networks · Computer Vision · Pytorch

Best deep CNN architectures and their principles: from AlexNet to EfficientNet

How convolutional neural networks work? What are the principles behind designing one CNN architecture? How did we go from AlexNet to EfficientNet?

Medical · Computer Vision

Transfer learning in medical imaging: classification and segmentation

What is transfer learning? How can it help us classify and segment different types of medical images? Are pretrained computer vision models useful for medical imaging tasks? How is 2D image classification different from 3D MRI segmentation in terms of transfer learning?

Medical · Computer Vision

Deep learning in MRI beyond segmentation: Medical image reconstruction, registration, and synthesis

How can deep learning revolutionize medical image analysis beyond segmentation? In this article, we will see a couple of interesting applications in medical imaging such as medical image reconstruction, image synthesis, super-resolution, and registration in medical images

Medical · Computer Vision

Introduction to 3D medical imaging for machine learning: preprocessing and augmentations

Learn how to apply 3D transformations for medical image preprocessing and augmentation, to setup your awesome deep learning pipeline

Computer Vision · Unsupervised Learning

Self-supervised representation learning on videos

In this article, we dive into the state-of-the-art methods on self-supervised representation learning in computer vision, by carefully reviewing the fundamentals concepts of self-supervision on learning video representations.

Medical · Computer Vision

Understanding coordinate systems and DICOM for deep learning medical image analysis

Multiple introductory concepts regarding deep learning in medical imaging, such as coordinate system and dicom data extraction from the machine learning perspective.

Convolutional Neural Networks · Computer Vision

Understanding the receptive field of deep convolutional networks

An intuitive guide on why it is important to inspect the receptive field, as well as how the receptive field affect the design choices of deep convolutional networks.

Generative Learning · Computer Vision

Deepfakes: Face synthesis with GANs and Autoencoders

A closer look on Deepfakes: face sythesis with StyleGAN, face swap with XceptionNet and facial attributes and expression manipulation with StarGAN

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - semantic image synthesis and learning a generative model from a single image

The sixth article-series of GAN in computer vision - we explore semantic image synthesis and learning a generative model from a single image

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - self-supervised adversarial training and high-resolution image synthesis with style incorporation

The fifth article-series of GAN in computer vision - we discuss self-supervision in adversarial training for unconditional image generation as well as in-layer normalization and style incorporation in high-resolution image synthesis.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - 2K image and video synthesis, and large-scale class-conditional image generation

The fourth article-series of GAN in computer vision - we explore 2K image generation with a multi-scale GAN approach, video synthesis with temporal consistency, and large-scale class-conditional image generation in ImageNet.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - Improved training with Wasserstein distance, game theory control and progressively growing schemes

The third article-series of GAN in computer vision - we encounter some of the most advanced training concepts such as Wasserstein distance, adopt a game theory aspect in the training of GAN, and study the incremental/progressive generative training to reach a megapixel resolution.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - Conditional image synthesis and 3D object generation

The second article of the GANs in computer vision series - looking deeper in generative adversarial networks, mode collapse, conditional image synthesis, and 3D object generation, paired and unpaired image to image generation.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - Introduction to generative learning

The first article of the GANs in computer vision series - an introduction to generative learning, adversarial learning, gan training algorithm, conditional image generation, mode collapse, mutual information

Medical · Computer Vision · Pytorch

Deep learning in medical imaging - 3D medical image segmentation with PyTorch

The basic MRI foundations are presented for tensor representation, as well as the basic components to apply a deep learning method that handles the task-specific problems(class imbalance, limited data). Moreover, we present some features of the open source medical image segmentation library. Finally, we discuss our preliminary experimental results and provide sources to find medical imaging data.

Computer Vision

Human Pose Estimation

An overview of the most popular models for performing 2D or 3D Human Pose Estimation

Convolutional Neural Networks · Computer Vision

Localization and Object Detection with Deep Learning

Explain RCNN, Fast RCNN and Faster RCNN

Convolutional Neural Networks · Computer Vision

Semantic Segmentation in the era of Neural Networks

Semantic segmentation with deep learning

Convolutional Neural Networks · Computer Vision

YOLO - You only look once (Single shot detectors)

Single shot detectors and how YOLO is used for object detection and localization

Computer Vision

Self-driving cars using Deep Learning

How self driving cars work, why Deep Learning made them a reality and how to program one (sort of)