Analytics Vidhya

MARCH 10, 2020

Starting your Deep Learning Career? Deep learning can be a complex and daunting field for newcomers. Concepts like hidden layers, convolutional neural networks, backpropagation. The post Getting into Deep Learning? Here are 5 Things you Should Absolutely Know appeared first on Analytics Vidhya.

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Analytics Vidhya

DECEMBER 31, 2023

A lightweight convolutional neural network (CNN) architecture, MobileNetV2, is specifically […] The post What is MobileNetV2? This article explores MobileNetV2’s architecture, training methodology, performance assessment, and practical implementation. What is MobileNetV2?

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Unite.AI

OCTOBER 2, 2024

Machine learning can analyze these datasets yet preparing them for analysis can be time-consuming and cumbersome. This article examines how Microsoft’s TorchGeo facilitates the processing of geospatial data, enhancing accessibility for machine learning experts.

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Analytics Vidhya

MAY 27, 2023

Introduction The UNet is the first model that comes to mind these days whenever we want to use image segmentation in machine learning. Extensive medical imaging, autonomous driving, and satellite imaging applications are all supported by the encoder-decoder convolutional neural network UNet.

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Marktechpost

MAY 10, 2024

Redundant execution introduces the concept of a hybrid (convolutional) neural network designed to facilitate reliable neural network execution for safe and dependable AI. The method has scope for further extension to more complex neural network architectures and applications with additional optimization.

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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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Analytics Vidhya

APRIL 15, 2024

Introduction Welcome to an in-depth exploration of ship classification using Convolutional Neural Networks (CNNs) with the Analytics Vidhya hackathon dataset. CNNs are a cornerstone of image-related tasks, known for their ability to learn hierarchical representations of images.

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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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Flipboard

FEBRUARY 2, 2023

Learn the basics of machine learning, including classification, SVM, decision tree learning, neural networks, convolutional, neural networks, boosting, and K nearest neighbors.

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Unite.AI

NOVEMBER 6, 2023

With these advancements, it’s natural to wonder: Are we approaching the end of traditional machine learning (ML)? In this article, we’ll look at the state of the traditional machine learning landscape concerning modern generative AI innovations. What is Traditional Machine Learning? What are its Limitations?

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Marktechpost

JUNE 9, 2024

Researchers at the Institute of Biomedical Engineering, TU Dresden, developed a deep learning architecture, xECGArch, for interpretable ECG analysis. xECGArch uniquely separates short-term (morphological) and long-term (rhythmic) ECG features using two independent Convolutional Neural Networks CNNs.

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Analytics Vidhya

FEBRUARY 16, 2022

Since 2012 after convolutional neural networks(CNN) were introduced, we moved away from handcrafted features to an end-to-end approach using deep neural networks. The post Classification without Training Data: Zero-shot Learning Approach appeared first on Analytics Vidhya.

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Marktechpost

JANUARY 9, 2024

It mentions the under-utilization of the Siamese neural network technique in recent studies on multimodal medical image classification, which motivates this study. TwinCNN combines a twin convolutional neural network framework with a hybrid binary optimizer for multimodal breast cancer digital image classification.

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Marktechpost

JANUARY 13, 2024

1/n) pic.twitter.com/LSXmEQiD2K — Zhuang Liu (@liuzhuang1234) January 8, 2024 The post How to Choose the Right Vision Model for Your Specific Needs: Beyond ImageNet Accuracy – A Comparative Analysis of Convolutional Neural Networks and Vision Transformer Architectures appeared first on MarkTechPost.

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Marktechpost

DECEMBER 10, 2024

Artificial Neural Networks (ANNs) have become one of the most transformative technologies in the field of artificial intelligence (AI). Modeled after the human brain, ANNs enable machines to learn from data, recognize patterns, and make decisions with remarkable accuracy. How Do Artificial Neural Networks Work?

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Flipboard

NOVEMBER 16, 2024

Raw images are processed and utilized as input data for a 2-D convolutional neural network (CNN) deep learning classifier, demonstrating an impressive 95% overall accuracy against new images. The glucose predictions done by CNN are compared with ISO 15197:2013/2015 gold standard norms.

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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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Marktechpost

SEPTEMBER 17, 2024

In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and time. One of the central challenges in this field is the extended time needed to train complex neural networks.

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Marktechpost

SEPTEMBER 10, 2023

The post Unlocking the Secrets of Catalytic Performance with Deep Learning: A Deep Dive into the ‘Global + Local’ Convolutional Neural Network for High-Precision Screening of Heterogeneous Catalysts appeared first on MarkTechPost. If you like our work, you will love our newsletter.

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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. As the data in a training set is processed, the neural network learns how to predict the outcome. Several types of networks exist.

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Marktechpost

MAY 5, 2024

In recent years, the demand for AI and Machine Learning has surged, making ML expertise increasingly vital for job seekers. Machine Learning with Python This course covers the fundamentals of machine learning algorithms and when to use each of them. and evaluating the same.

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Marktechpost

OCTOBER 4, 2024

Ready Tensor conducted an extensive benchmarking study to evaluate the performance of 25 machine learning models on five distinct datasets to improve time series step classification accuracy in their latest publication on Time Step Classification Benchmarking. Let’s collaborate!

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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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SAS Software

APRIL 27, 2023

In her first blog post, SAS' Mu He shows you how to train a convolutional neural network that can accurately detect patients with COVID-19 using the transfer learning technique. The post Using SAS Viya Machine Learning to classify COVID from non-COVID appeared first on SAS Blogs.

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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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AI News

JULY 27, 2023

The collaboration combines the strengths of three industry leaders: Graphcore, renowned for its Intelligence Processing Units (IPUs) hardware; UbiOps, a powerful machine learning operations (MLOps) platform; and Gcore Cloud, known for its robust cloud infrastructure.

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Marktechpost

NOVEMBER 27, 2024

In today’s world, you’ve probably heard the term “Machine Learning” more than once. Machine Learning, a subset of Artificial Intelligence, has emerged as a transformative force, empowering machines to learn from data and make intelligent decisions without explicit programming. housing prices, stock prices).

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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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Marktechpost

OCTOBER 8, 2024

They were recognized for their groundbreaking work in developing foundational machine learning technologies using artificial neural networks—work that has had a transformative impact on both the fields of physics and artificial intelligence.

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Marktechpost

APRIL 11, 2024

MIT researchers have proposed a method that combines first-principles calculations and machine learning to address the challenge of computationally expensive and intractable calculations required to understand the thermal conductivity of semiconductors, specifically focusing on diamonds.

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NVIDIA

OCTOBER 8, 2024

A recently released joint research paper by Yale, Moderna and NVIDIA reviews how techniques from quantum machine learning (QML) may enhance drug discovery methods by better predicting molecular properties. The study focuses on how future quantum neural networks can use quantum computing to enhance existing AI techniques.

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Unite.AI

SEPTEMBER 21, 2023

Some prominent AI techniques include neural networks, convolutional neural networks, transformers, and diffusion models. AI and machine learning (ML) algorithms are capable of the following: Analyzing transaction patterns to detect fraudulent activities made by bots. What is Blockchain?

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AI Weekly

JULY 27, 2023

bmj.com How AI can use classroom conversations to predict academic success By analyzing the classroom dialogs of these children, scientists at Tsinghua University developed neural network models to predict what behaviors may lead to a more successful student. Our Oppenheimer Moment: The Creation of A.I.

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Marktechpost

DECEMBER 24, 2023

In this critical realm, the transformative power of machine learning is reshaping the landscape. As the demand for sustainable agriculture grows, machine learning emerges as a vital force, reshaping the future of food security and cultivation.

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Towards AI

MARCH 17, 2023

Last time I showed you how to train a simple PyTorch model, this was an introduction to PyTorch where I showed you how to train an MNIST classifier with Convolutional Neural Networks. [link] Welcome everyone back to my other tutorial. We achieved a high accuracy rate of 97–98%, which means it’s very accurate.

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Marktechpost

NOVEMBER 16, 2024

Over two weeks, you’ll learn to extract features from images, apply deep learning techniques for tasks like classification, and work on a real-world project to detect facial key points using a convolutional neural network (CNN). Key topics include CNNs, RNNs, SLAM, and object tracking.

Computer Vision 104

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Unite.AI

SEPTEMBER 3, 2024

Computational power has become a critical factor in pushing the boundaries of what's possible in machine learning. As models grow more complex and datasets expand exponentially, traditional CPU-based computing often falls short of meeting the demands of modern machine learning tasks.

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