Dlabs.ai

NOVEMBER 16, 2020

Suguard is an internal project we’ve been developing since 2014, which is when we founded DiabetesLab : our second company focused on creating advanced software that helps people manage an illness using AI. The technology uses convolutional neural networks to indicate likely issues on a patient’s retina, boasting accuracy levels of 92.3%

Artificial Intelligence 52

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Lexalytics

APRIL 5, 2021

This would change in 1986 with the publication of “Parallel Distributed Processing” [ 6 ], which included a description of the backpropagation algorithm [ 7 ]. Note that Geoff Hinton was a co-author on this paper: his interest in neural networks was finally vindicated. The figure above shows a back-propagation network.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Viso.ai

MAY 31, 2024

Pascal VOC (which stands for Pattern Analysis, Statistical Modelling, and Computational Learning Visual Object Classes) is an open-source image dataset for a number of visual object recognition algorithms. As a result of Pascal VOC, researchers, and developers were able to compare various algorithms and methods on an entity basis.

Computer Vision 52

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52

Viso.ai

JULY 17, 2024

Background and History of Neural Style Transfer NST is an example of an image styling problem that has been in development for decades, with image analogies and texture synthesis algorithms paving foundational work for NST. Layer Reconstruction in VGG-19 network for style transfer. Here is the journey of NST. Gatys et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Viso.ai

DECEMBER 3, 2023

This article will explore the latest advances in pose analytics algorithms and AI vision techniques, their applications and use cases, and their limitations. Today, the most powerful image processing models are based on convolutional neural networks (CNNs). Definition: What is pose estimation?

Deep Learning 98

Deep Learning Computer Vision Neural Network Robotics 98

Viso.ai

DECEMBER 6, 2023

Modern computer vision research is producing novel algorithms for various applications, such as facial recognition, autonomous driving, annotated surgical videos, etc. For instance, CV algorithms can understand Light Detection and Ranging (LIDAR) data for enhanced perceptions of the environment. Get a demo here.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Google Research AI blog

JANUARY 18, 2023

Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. The neural network perceives an image, and generates a sequence of tokens for each object, which correspond to bounding boxes and class labels.

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John Snow Labs

MAY 23, 2023

This is because NLP technology enables the VQA algorithm to not only understand the question posed to it about the input image, but also to generate an answer in a language that the user (asking the question) can easily understand. The first VQA dataset was DAQUAR, released in 2014. For example, the question “what is in the image?”

Natural Language Processing 40

Natural Language Processing Deep Learning NLP Convolutional Neural Networks 40

Mlearning.ai

JUNE 8, 2023

Use algorithm to determine closeness/similarity of points. Images can be embedded using models such as convolutional neural networks (CNNs) , Examples of CNNs include VGG , and Inception. Doc2Vec: introduced in 2014, adds on to the Word2Vec model by introducing another ‘paragraph vector’. using its Spectrogram ).

Machine Learning 52

Machine Learning BERT Neural Network OpenAI 52

Marek Rei

NOVEMBER 12, 2019

Evaluations on CoNLL 2014 and JFLEG show a considerable improvement over previous best results of neural models, making this work comparable to state-of-the art on error correction. Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks Awni Y. Tison, Codie Bourn, Mintu P. Turakhia, Andrew Y.

Machine Learning 52

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ML Review

MAY 3, 2018

17] “ LipNet ” introduces the first approach for an end-to-end lip reading algorithm at sentence level. The combination of CNNs and RNNs in the network — itself a hark back to our comments around the lego-like approach of deep learning research — is, perhaps, more evidence for the soon-to-be-primacy of differential programming.

Neural Network 52

Neural Network Computer Vision Deep Learning NLP 52

Heartbeat

APRIL 18, 2023

HAR systems typically use machine learning algorithms to learn and classify human actions based on the visual features extracted from the input data. The VGG model The VGG ( Visual Geometry Group ) model is a deep convolutional neural network architecture for image recognition tasks. Zisserman and K.

Convolutional Neural Networks 52

Convolutional Neural Networks Deep Learning Neural Network Machine Learning 52

NLP People

JULY 24, 2019

As the following chart shows, research activity has been flourishing in the past years: Figure 1: Paper quantity published at the ACL conference by years In the following, we summarize some core trends in terms of data strategies, algorithms, tasks as well as multilingual NLP. Neural Networks are the workhorse of Deep Learning (cf.

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52

Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Unite.AI

JUNE 25, 2024

These techniques involve training neural networks on large datasets of images and videos, enabling them to generate synthetic media that closely mimics real-life appearances and movements. The advent of GANs in 2014 marked a significant milestone, allowing the creation of more sophisticated and hyperrealistic deepfakes.

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