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.

Deep Learning 400

Deep Learning Convolutional Neural Networks Neural Network Python 400

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.

Machine Learning 278

Machine Learning Convolutional Neural Networks Neural Network Data Scientist 278

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.

Convolutional Neural Networks 323

Convolutional Neural Networks Neural Network Machine Learning Python 323

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 102

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 102

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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Convolutional Neural Networks Neural Network AI AI 122

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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Convolutional Neural Networks Neural Network Data Analysis Data Science 303

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.

Convolutional Neural Networks 103

Convolutional Neural Networks Neural Network Natural Language Processing Artificial Intelligence 103

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.

Neural Network 75

Neural Network Convolutional Neural Networks AI AI 75

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?

Convolutional Neural Networks 329

Convolutional Neural Networks Neural Network Data Science Artificial Intelligence 329

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.

Convolutional Neural Networks 271

Convolutional Neural Networks Neural Network Machine Learning Data Science 271

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.

Convolutional Neural Networks 174

Convolutional Neural Networks Machine Learning Neural Network 174

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?

Machine Learning 204

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 204

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.

Convolutional Neural Networks 271

Convolutional Neural Networks Neural Network Computer Vision Data Science 271

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.

Convolutional Neural Networks 122

Convolutional Neural Networks Neural Network Deep Learning Big Data 122

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.

Convolutional Neural Networks 114

Convolutional Neural Networks Neural Network Deep Learning Algorithm 114

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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Convolutional Neural Networks Algorithm Neural Network Computer Vision 147

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.

Convolutional Neural Networks 94

Convolutional Neural Networks Neural Network Deep Learning AI 94

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.

Convolutional Neural Networks 82

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 82

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.

Convolutional Neural Networks 234

Convolutional Neural Networks Neural Network Big Data Deep Learning 234

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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Convolutional Neural Networks Neural Network Computer Vision AI Research 129

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.

Convolutional Neural Networks 102

Convolutional Neural Networks Neural Network Automation Machine Learning 102

Flipboard

JANUARY 31, 2025

A new neural network process has designed wireless chips that can outperform existing ones. This convolutional neural network analyzes the desired chip properties then designs backward. That might be a problem. Much of AI news is hype, but this is open access, peer reviewed research in a reputable

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Convolutional Neural Networks Neural Network AI AI 181

Flipboard

MARCH 24, 2025

This paper investigates the role of multidimensional Convolutional Neural Network (CNN) architectures: 1D-CNN, 2D-CNN and 3D-CNN, using the DWT subbands of sMRI data. 1D-CNN involves energy features extracted from the CD subband of sMRI data.

Convolutional Neural Networks 73

Convolutional Neural Networks Neural Network Machine Learning 73

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.

Neural Network 111

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 111

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?

Neural Network 107

Neural Network Convolutional Neural Networks Natural Language Processing Algorithm 107

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.

Neural Network 263

Neural Network Convolutional Neural Networks Large Language Models Computer Vision 263

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.

Convolutional Neural Networks 117

Convolutional Neural Networks Neural Network Deep Learning ML 117

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?

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

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.

Convolutional Neural Networks 115

Convolutional Neural Networks Machine Learning Neural Network Data Mining 115

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!

Neural Network 103

Neural Network Machine Learning Convolutional Neural Networks Categorization 103

Flipboard

FEBRUARY 3, 2025

Although several computer-aided cholelithiasis diagnosis approaches have been introduced in the literature, their use is limited because Convolutional Neural Network (CNN) models are black box in nature. Accurate and precise identification of cholelithiasis is essential for saving the lives of millions of people worldwide.

Convolutional Neural Networks 65

Convolutional Neural Networks Neural Network Explainability Machine Learning 65

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.

Machine Learning 117

Machine Learning Python Neural Network Convolutional Neural Networks 117

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.

Neural Network 246

Neural Network Convolutional Neural Networks Natural Language Processing Robotics 246

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.

Machine Learning 107

Machine Learning Neural Network Convolutional Neural Networks Artificial Intelligence 107

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.

Machine Learning 52

Machine Learning Convolutional Neural Networks Neural Network Natural Language Processing 52

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.

Machine Learning 107

Machine Learning Convolutional Neural Networks Neural Network AI 107

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.

Convolutional Neural Networks 60

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 60