Marktechpost

JULY 24, 2023

This model predicts rainfall for the full satellite area using convolutional neural networks’ spatial invariance, even if radar data is only available for a smaller area. The first model, sat2rad, is a U-Net-based deep learning model that estimates rainfall in the current satellite frame time step.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network ML 52

Viso.ai

MARCH 11, 2024

YOLO in 2015 became the first significant model capable of object detection with a single pass of the network. The previous approaches relied on Region-based Convolutional Neural Network (RCNN) and sliding window techniques. What is YOLO?

Explainability 52

Explainability Convolutional Neural Networks Neural Network Computer Vision 52

Viso.ai

FEBRUARY 27, 2024

Farhadi, signifying a step forward in the real-time object detection space, outperforming its predecessor – the Region-based Convolutional Neural Network (R-CNN). It is a single-pass algorithm having only one neural network to predict bounding boxes and class probabilities using a full image as input. Divvala, R.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Python 52

ML Review

JUNE 4, 2018

These new approaches generally; Feed the image into a Convolutional Neural Network (CNN) for encoding, and run this encoding into a decoder Recurrent Neural Network (RNN) to generate an output sentence. The complete set of generated words is the output sequence (or sentence) of the network.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

John Snow Labs

MAY 23, 2023

VQA frameworks combine two Deep Learning architectures to deliver the final answer: Convolutional Neural Networks (CNN) for image recognition and Recurrent Neural Network (RNN) (and its special variant Long Short Term Memory networks or LSTM) for NLP processing.

Natural Language Processing 40

Natural Language Processing Deep Learning NLP Convolutional Neural Networks 40

Lexalytics

APRIL 5, 2021

Around this time (early 2016), our management team realized that to maintain relevance as a company, we would need to be able to incorporate even more ML into our product. The CNN was a 6-layer neural net with 132 convolution kernels and (don’t laugh!) 90,575 trainable parameters, placing it in the small-feature regime.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Explosion

NOVEMBER 9, 2016

2016) introduce an attention mechanism that takes two sentence matrices, and outputs a single vector: Yang et al. 2016) introduce an attention mechanism that takes a single matrix and outputs a single vector. 2016) presented a model that achieved 86.8% 2016) presented a model that achieved 86.8% 2016) HN-ATT 68.2

Deep Learning 52

Deep Learning NLP Convolutional Neural Networks Neural Network 52

Marek Rei

JANUARY 17, 2018

The only filter that I applied was to exclude papers older than 2016, as the goal is to give an overview of the more recent work. NAACL 2016. Neural activity by brain region, from Wehbe et al. NAACL 2016. The papers are not selected or ordered based on any criteria. I set out to summarise 50 papers. Copenhagen.

Machine Learning 52

Machine Learning NLP Neural Network Convolutional Neural Networks 52

Viso.ai

DECEMBER 18, 2023

YOLO’s architecture was a significant revolution in the real-time object detection space, surpassing its predecessor – the Region-based Convolutional Neural Network (R-CNN). The backbone is a pre-trained Convolutional Neural Network (CNN) that extracts low, medium, and high-level feature maps from an input image.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Algorithm 52

Snorkel AI

MARCH 1, 2023

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Radford et al. 2016) This paper introduced DCGANs, a type of generative model that uses convolutional neural networks to generate images with high fidelity. Attention Is All You Need Vaswani et al.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

deepsense.ai

MAY 7, 2023

This solution is based on several Convolutional Neural Networks that work in a cascade fashion to locate the face with some landmarks in an image. The first network is called a Proposal Network – it parses the image and selects several bounding boxes that surround an object of interest: a face, in our case.

Neural Network 52

Neural Network Convolutional Neural Networks Explainability Deep Learning 52

Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. spaCy’s default token-vector encoding settings are a depth 4 convolutional neural network with width 96, and hash embeddings with 2000 rows.

NLP 52

NLP Convolutional Neural Networks Neural Network Natural Language Processing 52

Viso.ai

MAY 20, 2023

Most algorithms use a convolutional neural network (CNN) to extract features from the image to predict the probability of learned classes. The original YOLO object detector was first released in 2016. YOLOv7 applied for computer vision in Aviation – built on Viso Suite What is YOLO in computer vision?

Algorithm 52

Algorithm Computer Vision Deep Learning Neural Network 52

Sebastian Ruder

JANUARY 19, 2021

2016 ; Webster et al.,  While Transformers have achieved large success in NLP, they were—up until recently—less successful in computer vision where convolutional neural networks (CNNs) still reigned supreme. Pre-trained language models were found to be prone to generating toxic language ( Gehman et al.,

NLP 52

NLP ML Computer Vision 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. Thus, positioning him as one of the top AI influencers in the world.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Google Research AI blog

JANUARY 18, 2023

One trend that started with our work on Vision Transformers in 2020 is to use the Transformer architecture in computer vision models rather than convolutional neural networks. Top Computer Vision Computer vision continues to evolve and make rapid progress.

Computer Vision 132

Computer Vision Auto-classification Large Language Models Neural Network 132

ML Review

MAY 3, 2018

2016) — “ LipNet: End-to-End Sentence-level Lipreading.” [17] 22] On a high level in the architecture, the frames extracted from a video sequence are processed in small sets within a Convolutional Neural Network (CNN), [23] while an LSTM-variant runs on the CNN output sequentially to generate output characters.

Neural Network 52

Neural Network Computer Vision Deep Learning Convolutional Neural Networks 52