CNN / Neural Networks and Deep Learning

Convolutional Neural Networks (CNN): How They Work, Step by Step

25 October 2026

Convolutional Neural Networks (CNN): How They Work, Step by Step

A convolutional neural network (CNN, or ConvNet) is a type of neural network designed for data with a grid structure, above all images. Instead of connecting every input pixel to…

Artificial Intelligence System Predicts Worsening Patient in Emergency Room

14 May 2021

14 May 2021

Artificial Intelligence System Predicts Worsening Patient in Emergency Room

14 May 2021

A group of researchers has created an approach to automatically predict the deterioration of patients’ condition using a neural network. The system was trained on chest x-rays and non-visual clinical…

CSTR neural network recognizes text in scene images

1 March 2021

CSTR neural network recognizes text in scene images

CSTR is a convolutional neural network that recognizes text in scene images. The previous work considers the problem of text recognition on a scene image as a segmentation and seq2seq…

Deep Neural Network Learns to “See” Through Obstructions

15 April 2020

15 April 2020

Deep Neural Network Learns to “See” Through Obstructions

15 April 2020

A group of researchers led by Yu-Lun Liu has proposed a deep learning-based method that removes unwanted obstructions such as raindrops, fences or window reflections from short videos. Very often,…

ResNet (34, 50, 101): Residual CNNs for Image Classification Tasks

23 January 2019

ResNet (34, 50, 101): Residual CNNs for Image Classification Tasks

ResNet is a short name for a residual network, but what’s residual learning? Deep convolutional neural networks have achieved the human level image classification result. Deep networks extract low, middle…

R-CNN – Neural Network for Object Detection and Semantic Segmentation

29 November 2018

R-CNN – Neural Network for Object Detection and Semantic Segmentation

Computer vision is an interdisciplinary field that has been gaining huge amounts of traction in recent years (since CNN), and self-driving cars have taken center stage. One of the most…

U-Net: Image Segmentation Network

23 November 2018

U-Net: Image Segmentation Network

U-Net is considered one of the standard CNN architectures for image classification tasks, when we need not only to define the whole image by its class but also to segment areas of…

VGG16 – Convolutional Network for Classification and Detection

20 November 2018

VGG16 – Convolutional Network for Classification and Detection

VGG16 is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper “Very Deep Convolutional Networks for Large-Scale Image Recognition”.…

AlexNet – ImageNet Classification with Deep Convolutional Neural Networks

29 October 2018

AlexNet – ImageNet Classification with Deep Convolutional Neural Networks

AlexNet is the name of a convolutional neural network which has had a large impact on the field of machine learning, specifically in the application of deep learning to machine vision. It famously won the…

Temporal Relational Reasoning in Videos

25 September 2018

Temporal Relational Reasoning in Videos

The ability to reason about the relations between entities over time is crucial for intelligent decision-making. Temporal relational reasoning allows intelligent species to analyze the current situation relative to the…

Inferring a 3D Human Pose out of a 2D Image with FBI

16 July 2018

3D pose estimation based on 2D joints and Forward-or-Backward Information (FBI) for each bone

Inferring a 3D Human Pose out of a 2D Image with FBI

Autonomous driving, virtual reality, human-computer interaction and video surveillance — these are all application scenarios, where you would like to derive a 3D human pose out of a single RGB…

A New Method for Image De-blurring

21 June 2018

A New Method for Image De-blurring

When we use a camera, we want the recorded image to be a faithful representation of what we see in front of us. However, very often images contain blur, and…

Human Rights Violations Recognition in Images Using CNN Features

18 May 2018

Human Rights Violations Recognition in Images Using CNN Features

Human rights violations have been unfolding during the entire human history, while nowadays they increasingly appear in many different forms around the world. Human rights violations refer to the actions…

Image Inpainting for Irregular Holes Using Partial Convolutions

8 May 2018

Image Inpainting for Irregular Holes Using Partial Convolutions

Deep learning is growing very fast and it is one of the fast-growing areas of artificial intelligence. It has been used in many fields extensively including real-time object detection, image…

Materials for Masses: SVBRDF Acquisition with a Single Mobile Phone Image

3 May 2018

Materials for Masses: SVBRDF Acquisition with a Single Mobile Phone Image

A wide variety of images around us are the outcome of interactions between lighting, shapes and materials. In recent years, the advent of convolutional neural networks (CNN) has led to…

Neural Network Has Learned to Separate Individuals’ Speech on Video

13 April 2018

Neural Network Has Learned to Separate Individuals’ Speech on Video

The fact that our brain in a noisy environment can effectively focus on a particular speaker, “turning off” background sounds — is no secret. This phenomenon even received the popular…

How Has MS Voxel Deep Network Managed to Improve 3D Objects Recognition Using Cloud Map Only

12 April 2018

How Has MS Voxel Deep Network Managed to Improve 3D Objects Recognition Using Cloud Map Only

Mobile Laser Scanning (MLS) systems can now scan large areas, like cities or even countries. The produced 3D point clouds can be used as maps for autonomous systems. To do…