Viso.ai

MARCH 26, 2024

Arguably, one of the most pivotal breakthroughs is the application of Convolutional Neural Networks (CNNs) to financial processes. This drastically enhanced the capabilities of computer vision systems to recognize patterns far beyond the capability of humans. Applications of Computer Vision in Finance No.

Computer Vision 52

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Flipboard

MARCH 27, 2023

Project Structure Accelerating Convolutional Neural Networks Parsing Command Line Arguments and Running a Model Evaluating Convolutional Neural Networks Accelerating Vision Transformers Evaluating Vision Transformers Accelerating BERT Evaluating BERT Miscellaneous Summary Citation Information What’s New in PyTorch 2.0?

Neural Network 117

Neural Network Convolutional Neural Networks BERT Computer Vision 117

TensorFlow

MARCH 29, 2023

ZenDNN is purpose-built to help deep learning application and framework developers improve inference performance on AMD EPYC CPUs across an array of workloads, including computer vision, natural language processing, and recommender systems. TF-ZenDNN We have integrated ZenDNN into high-level AI frameworks for ease of use.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing Computer Vision 52

Topbots

OCTOBER 4, 2023

Image processing : Predictive image processing models, such as convolutional neural networks (CNNs), can classify images into predefined labels (e.g., Masking in BERT architecture ( illustration by Misha Laskin ) Another common type of generative AI model are diffusion models for image and video generation and editing.

Generative AI 118

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 118

Viso.ai

APRIL 26, 2024

Object detection systems typically use frameworks like Convolutional Neural Networks (CNNs) and Region-based CNNs (R-CNNs). Concept of Convolutional Neural Networks (CNN) However, in prompt object detection systems, users dynamically direct the model with many tasks it may not have encountered before.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Unite.AI

APRIL 2, 2024

These problems, commonly referred to as degradations in low-level computer vision, can arise from difficult environmental conditions like heat or rain or from limitations of the camera itself. These deep learning image restoration models propose to use neural networks based on Transformers and Convolutional Neural Networks.

Computer Vision 130

Computer Vision Neural Network Convolutional Neural Networks Deep Learning 130

Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). Viso Suite: The only truly end-to-end computer vision solution, Viso Suite eliminates the need for point solutions. Viso Suite is the end-to-End, No-Code Computer Vision Solution.

Deep Learning 52

Deep Learning Computer Vision Neural Network Natural Language Processing 52

Unite.AI

AUGUST 2, 2023

To overcome the challenge presented by single modality models & algorithms, Meta AI released the data2vec, an algorithm that uses the same learning methodology for either computer vision , NLP or speech. For computer vision, the model practices block-wise marking strategy.

Computer Vision 246

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Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. This article will cover the following topics: What is a Vision Transformer (ViT)?

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

ML Review

DECEMBER 16, 2019

NeurIPS’18 presented several papers with deep theoretical studies of building hyperbolic neural nets. Source: Chami et al Chami et al present Hyperbolic Graph Convolutional Neural Networks (HGCN) and Liu et al propose Hyperbolic Graph Neural Networks (HGNN). Top-5 accuracy grows from previous SOTA of 84.3%

Machine Learning 52

Machine Learning Neural Network Explainability NLP 52

Viso.ai

DECEMBER 18, 2023

ONNX is an open standard for representing computer vision and machine learning models. ONNX (Open Neural Network Exchange) is an open-source format that facilitates interoperability between different deep learning algorithms for simple model sharing and deployment. Microsoft Cognitive Toolkit (CNTK). Apache MXNet.

Explainability 52

Explainability Neural Network Deep Learning Machine Learning 52

Heartbeat

FEBRUARY 8, 2024

Cross-modal retrieval is a branch of computer vision and natural language processing that links visual and verbal descriptions. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are often employed to extract meaningful representations from images and text, respectively.

Neural Network 52

Neural Network Deep Learning Convolutional Neural Networks Computer Vision 52

Pragnakalp

JANUARY 1, 2024

Compared with traditional recurrent neural networks (RNNs) and convolutional neural networks (CNNs), transformers differ in their ability to capture long-range dependencies and contextual information. They’re used to perform or improve AI and NLP business tasks, as well as streamline enterprise workflows.

Natural Language Processing 52

Natural Language Processing Neural Network Convolutional Neural Networks LLM 52

Snorkel AI

MARCH 1, 2023

BERT BERT, an acronym that stands for “Bidirectional Encoder Representations from Transformers,” was one of the first foundation models and pre-dated the term by several years. BERT proved useful in several ways, including quantifying sentiment and predicting the words likely to follow in unfinished sentences.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Lexalytics

APRIL 5, 2021

While working as an RA in the computer vision group, I had the opportunity to sit in a robotic Humvee as it used Pomerleau’s code to drive around the University of Massachusetts’ stadium.) The CNN was a 6-layer neural net with 132 convolution kernels and (don’t laugh!) Hinton (again!)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

DataRobot Blog

MARCH 9, 2022

These embeddings are sometimes trained jointly with the model, but usually additional accuracy can be attained by using pre-trained embeddings such as Word2Vec, GloVe, BERT, or FastText.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Deep Learning 52

Sebastian Ruder

JANUARY 19, 2021

More recently, contrastive learning gained popularity in self-supervised representation learning in computer vision and speech ( van den Oord, 2018 ; Hénaff et al., A plethora of language-specific BERT models have been trained for languages beyond English such as AraBERT ( Antoun et al., 2020 ), RemBERT ( Chung et al.,

NLP 52

NLP ML Computer Vision Natural Language Processing 52

Marktechpost

JUNE 27, 2023

Since this is a crucial component of any deep learning or convolutional neural network system. Gaussian Error Linear Unit Function Many of the most popular NLP models, including BERT, ROBERTa, and ALBERT, are compatible with the GELU activation function.

Neural Network 52

Neural Network Convolutional Neural Networks Deep Learning NLP 52

ML Review

FEBRUARY 11, 2019

If you don’t know it already, NLP had a huge hype of transfer learning in this past 1 year, starting with ULMFit , ELMo , GLoMo , OpenAI transformer , BERT and recently Transformer-XL for further improving language modeling capabilities of the current state of the art.

Neural Network 52

Neural Network NLP Explainability Convolutional Neural Networks 52

Marktechpost

APRIL 20, 2024

Deep neural networks like convolutional neural networks (CNNs) have revolutionized various computer vision tasks, from image classification to object detection and segmentation. As models grew larger and more complex, their accuracy soared. Check out the Paper.

Machine Learning 96

Machine Learning Neural Network Convolutional Neural Networks Computer Vision 96

John Snow Labs

MAY 8, 2024

Nevertheless, the trajectory shifted remarkably with the introduction of advanced architectures like BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), including subsequent versions such as OpenAI’s GPT-3.

Large Language Models 40

Large Language Models Automation NLP Machine Learning 40

AWS Machine Learning Blog

FEBRUARY 24, 2023

This satisfies the strong MME demand for deep neural network (DNN) models that benefit from accelerated compute with GPUs. These include computer vision (CV), natural language processing (NLP), and generative AI models. The impact is more for models using a convolutional neural network (CNN).

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