Analytics Vidhya

OCTOBER 9, 2022

Introduction In recent times, whenever we wish to perform image segmentation in machine learning, the first model we think of is the U-Net. U-Net is an encoder-decoder convolutional neural network with […]. It has been revolutionary in performance improvement compared to previous state-of-the-art methods.

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Unite.AI

DECEMBER 26, 2024

These deep learning algorithms get data from the gyroscope and accelerometer inside a wearable device ideally worn around the neck or at the hip to monitor speed and angular changes across three dimensions. Where does this data come from? One stream of data can be collected through a system of discreet cameras, radars, and sensors.

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Marktechpost

MAY 13, 2024

Vision Transformers (ViT) and Convolutional Neural Networks (CNN) have emerged as key players in image processing in the competitive landscape of machine learning technologies. Convolutional Neural Networks (CNNs) CNNs have been the cornerstone of image-processing tasks for years.

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Marktechpost

JANUARY 13, 2024

There has been a dramatic increase in the complexity of the computer vision model landscape. Many models are now at your fingertips, from the first ConvNets to the latest Vision Transformers. Our work comprehensively compares common vision models on "non-standard" metrics. (1/n)

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Mlearning.ai

FEBRUARY 22, 2023

Machine learning interview preparation: computer vision, convolutional neural network, pooling, popular convolutional neural networks Continue reading on MLearning.ai »

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Flipboard

JANUARY 9, 2025

Empirical evidence shows that fully-connected neural networks in the infinite-width limit (lazy training) eventually outperform their finite-width counterparts in most computer vision tasks; on the other hand, modern architectures with convolutional layers often achieve optimal performances in the finite-width regime.

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Flipboard

JULY 31, 2023

In this post, we’ll show you the datasets you can use to build your machine learning projects. After you create a free account, you’ll have access to the best machine learning datasets. Importance and Role of Datasets in Machine Learning Data is king.

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ODSC - Open Data Science

FEBRUARY 10, 2025

A/V analysis and detection are some of machine learnings most practical applications. Many tools apply these capabilities to text-based data or network traffic, but audio and video use cases are also worthnoting. Choose an Appropriate Algorithm As with all machine learning processes, algorithm selection is also crucial.

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AI Weekly

OCTOBER 26, 2023

cryptopolitan.com Applied use cases Alluxio rolls out new filesystem built for deep learning Alluxio Enterprise AI is aimed at data-intensive deep learning applications such as generative AI, computer vision, natural language processing, large language models and high-performance data analytics. voxeurop.eu

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Viso.ai

DECEMBER 1, 2024

This article covers an extensive list of novel, valuable computer vision applications across all industries. Find the best computer vision projects, computer vision ideas, and high-value use cases in the market right now. provides Viso Suite , the world’s only end-to-end Computer Vision Platform.

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Marktechpost

SEPTEMBER 18, 2024

Traditional machine learning methods, such as convolutional neural networks (CNNs), have been employed for this task, but they come with limitations. Manual classification is slow and prone to inconsistencies due to the subjective nature of human judgment.

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Unite.AI

OCTOBER 17, 2024

Healthcare in the United States is in the early stages of a significant potential disruption due to the use of Machine Learning and Artificial Intelligence. Some of the earliest and most extensive work has occurred in the use of deep learning and computer vision models. Several types of networks exist.

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Pickl AI

SEPTEMBER 5, 2024

Summary: Convolutional Neural Networks (CNNs) are essential deep learning algorithms for analysing visual data. They automatically extract and learn features, making them ideal for tasks like image classification and object detection. What are Convolutional Neural Networks?

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Marktechpost

SEPTEMBER 9, 2024

Computer vision is rapidly transforming industries by enabling machines to interpret and make decisions based on visual data. Learning computer vision is essential as it equips you with the skills to develop innovative solutions in areas like automation, robotics, and AI-driven analytics, driving the future of technology.

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PyImageSearch

MARCH 30, 2023

If you want a gentle introduction to machine learning for computer vision, you’re in the right spot. Here at PyImageSearch we’ve been helping people just like you master deep learning for computer vision.

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Viso.ai

FEBRUARY 25, 2024

Image reconstruction is an AI-powered process central to computer vision. In this article, we’ll provide a deep dive into using computer vision for image reconstruction. About Us: Viso Suite is the end-to-end computer vision platform helping enterprises solve challenges across industry lines.

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Viso.ai

DECEMBER 20, 2023

In the field of computer vision, supervised learning and unsupervised learning are two of the most important concepts. In this guide, we will explore the differences and when to use supervised or unsupervised learning for computer vision tasks. What is supervised learning? About us: Viso.ai

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Unite.AI

AUGUST 2, 2023

Machine learning models have heavily relied on labeled data for training, and traditionally speaking, training models on labeled data yields accurate results. To tackle the annotation issue, developers came up with the concept of SSL or Self Supervised Learning. They require a high amount of computational power.

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Heartbeat

MARCH 14, 2023

The goal of computer vision research is to teach computers to recognize objects and scenes in their surroundings. In this article, I would like to take a look at the current challenges in the field of robotics and discuss the relevance and applications of computer vision in this area.

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AWS Machine Learning Blog

DECEMBER 14, 2023

To overcome this business challenge, ICL decided to develop in-house capabilities to use machine learning (ML) for computer vision (CV) to automatically monitor their mining machines. ICL’s computer vision use case For the prototyping engagement, ICL selected the use case for monitoring their mining screeners.

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Viso.ai

JANUARY 2, 2024

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Whether you’re a beginner or an experienced practitioner, this guide will provide insights into the mechanics of artificial neural networks and their applications.

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Marktechpost

MARCH 1, 2024

A key component of deep convolutional neural network training is feature normalization, which aims to increase stability, reduce internal covariate shifts, and boost network performance. Batch normalization is one of these that is frequently used, particularly in computer vision applications.

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Heartbeat

AUGUST 21, 2023

In this guide, we’ll talk about Convolutional Neural Networks, how to train a CNN, what applications CNNs can be used for, and best practices for using CNNs. What Are Convolutional Neural Networks CNN? CNNs learn geometric properties on different scales by applying convolutional filters to input data.

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Marktechpost

JUNE 3, 2024

Its AI courses offer hands-on training for real-world applications, enabling learners to effectively use Intel’s portfolio in deep learning, computer vision, and more. Introduction to Machine Learning This course covers machine learning basics, including problem-solving, model building, and key algorithms.

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Marktechpost

SEPTEMBER 24, 2024

The success of this model reflects a broader shift in computer vision towards machine learning approaches that leverage large datasets and computational power. Previously, researchers doubted that neural networks could solve complex visual tasks without hand-designed systems. by the next-best model.

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AWS Machine Learning Blog

MARCH 30, 2023

In this post, we introduce a new interactive tool called Snapper, powered by a machine learning (ML) model that reduces the effort required of annotators. ML model optimized for annotators A tremendous number of high-performing object detection models have been proposed by the computer vision community in recent years.

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Viso.ai

DECEMBER 19, 2023

This article covers everything you need to know about image classification – the computer vision task of identifying what an image represents. Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. It’s a powerful all-in-one solution for AI vision.

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Marktechpost

JANUARY 30, 2025

Contrastingly, agentic systems incorporate machine learning (ML) and artificial intelligence (AI) methodologies that allow them to adapt, learn from experience, and navigate uncertain environments. Image Embeddings: Convolutional neural networks (CNNs) or vision transformers can transform images into dense vector embedding.

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Marktechpost

SEPTEMBER 17, 2024

Although optimizers like Adam perform parameter updates iteratively to minimize errors gradually, the sheer size of models, especially in tasks like natural language processing (NLP) and computer vision, leads to long training cycles. This reduction translates into faster training and significant savings in computational resources.

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Pickl AI

JANUARY 29, 2025

Collaboration and sharing code can accelerate learning. Completing projects boosts confidence in using Deep Learning tools. What is Deep Learning? Deep Learning is a specialized subset of Artificial Intelligence (AI) and machine learning that employs multilayered artificial neural networks to analyze and interpret complex data.

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Heartbeat

DECEMBER 20, 2023

Whether you’re a seasoned AI researcher or a budding enthusiast in machine learning, the insights offered here will deepen your understanding and guide you in leveraging the full potential of CNNs in various applications. The net result of both of these scenarios is that early layers in the network become more challenging to train.

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Marktechpost

NOVEMBER 21, 2024

Vision Transformers (ViTs) have revolutionized computer vision by offering an innovative architecture that uses self-attention mechanisms to process image data. It has long been assumed that pre-training enhances downstream task performance by learning useful feature representations. Check out the Details.

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Viso.ai

DECEMBER 10, 2023

This article will cover image recognition, an application of Artificial Intelligence (AI), and computer vision. Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. Get a personalized demo. link] What is Image Recognition?

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Marktechpost

SEPTEMBER 12, 2023

Image-to-image translation (I2I) is an interesting field within computer vision and machine learning that holds the power to transform visual content from one domain into another seamlessly.

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Towards AI

MARCH 7, 2025

Limitations of ANNs: Move to Convolutional Neural Networks This member-only story is on us. The journey from traditional neural networks to convolutional architectures wasnt just a technical evolution it was a fundamental reimagining of how machines should perceive visual information.

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Marktechpost

JULY 31, 2024

TensorFlow is a powerful open-source framework for building and deploying machine learning models. Learning TensorFlow enables you to create sophisticated neural networks for tasks like image recognition, natural language processing, and predictive analytics.

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IBM Journey to AI blog

MAY 6, 2024

Machine learning and deep neural network models can effectively analyze this data to identify patterns, correlations and relationships, which is particularly useful for understanding a patient’s unique profile.

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