Analytics Vidhya

SEPTEMBER 27, 2022

Introduction My last blog discussed the “Training of a convolutional neural network from scratch using the custom dataset.” ” In that blog, I have explained: how to create a dataset directory, train, test and validation dataset splitting, and training from scratch. This blog is […].

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Marktechpost

OCTOBER 28, 2023

However, a common limitation of many machine learning models in this field is their lack of interpretability – they can predict outcomes accurately but struggle to explain how they arrived at those predictions. This innovative model has the potential to significantly enhance our understanding of this fundamental process.

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PyImageSearch

OCTOBER 28, 2024

Home Table of Contents NeRFs Explained: Goodbye Photogrammetry? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work?

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Explainability Neural Network Computer Vision Deep Learning 91

Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

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PyImageSearch

OCTOBER 14, 2024

This blog post is the 1st of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion (this blog post) 3D Reconstruction: Have NeRFs Removed the Need for Photogrammetry? The second blog post will introduce you to NeRFs , the neural network solution. The core idea?

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Explainability Computer Vision Deep Learning Algorithm 110

Unite.AI

NOVEMBER 6, 2023

Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models. Advances in neural network techniques have formed the basis for transitioning from machine learning to deep learning.

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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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Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Explainability is essential for accountability, fairness, and user confidence. Explainability also aligns with business ethics and regulatory compliance.

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Composite AI Explainability Black Box AI Explainable AI 179

Viso.ai

DECEMBER 18, 2023

As an Edge AI implementation, TensorFlow Lite greatly reduces the barriers to introducing large-scale computer vision with on-device machine learning, making it possible to run machine learning everywhere. About us: At viso.ai, we power the most comprehensive computer vision platform Viso Suite. What is TensorFlow?

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PyImageSearch

JANUARY 30, 2023

To learn about Computer Vision and Deep Learning for Education, just keep reading. Computer Vision and Deep Learning for Education Benefits Smart Content Artificial Intelligence can help teachers and research experts create innovative and personalized content for their students. Or requires a degree in computer science?

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Marktechpost

DECEMBER 13, 2024

Neural networks have become foundational tools in computer vision, NLP, and many other fields, offering capabilities to model and predict complex patterns. This understanding is essential for designing more efficient training algorithms and enhancing the interpretability and robustness of neural networks.

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Neural Network Machine Learning Computer Vision AI 73

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?

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Neural Network Convolutional Neural Networks BERT Deep Learning 159

NYU Center for Data Science

DECEMBER 3, 2024

The research revealed that regardless of whether a neural network is trained to recognize images from popular computer vision datasets like ImageNet or CIFAR, it develops similar internal patterns for processing visual information. The analogy to astrophysics is particularly apt.

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Neural Network Computer Scientist Computer Vision Explainability 60

IBM Journey to AI blog

SEPTEMBER 24, 2024

“AI could lead to more accurate and timely predictions, especially for spotting diseases early,” he explains, “and it could help cut down on carbon footprints and environmental impact by improving how we use energy and resources.” A computer doesn’t have these problems.

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AI Weekly

JANUARY 18, 2024

Powered by superai.com In the News Bill Gates explains how AI will change our lives in 5 years It’s no secret that Bill Gates is bullish on artificial intelligence, but he’s now predicting that the technology will be transformative for everyone within the next five years.

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Marktechpost

DECEMBER 5, 2023

The Hierarchically Gated Recurrent Neural Network (HGRN) technique developed by researchers from the Shanghai Artificial Intelligence Laboratory and MIT CSAI addresses the challenge of enhancing sequence modeling by incorporating forget gates in linear RNNs. Check out the Paper , Github, and Project.

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Unite.AI

JULY 12, 2024

Photomath Photomath is a popular mobile app that uses advanced computer vision and artificial intelligence to provide instant solutions to math problems. This feature uses a neural network model that has been trained on over 100,000 images of handwritten math expressions, achieving an impressive 98% accuracy rate.

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Heartbeat

JUNE 27, 2023

Photo by Resource Database on Unsplash Introduction Neural networks have been operating on graph data for over a decade now. Neural networks leverage the structure and properties of graph and work in a similar fashion. Graph Neural Networks are a class of artificial neural networks that can be represented as graphs.

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Neural Network Convolutional Neural Networks Auto-classification Deep Learning 59

Marktechpost

MARCH 11, 2024

However, understanding their information-flow dynamics, learning mechanisms, and interoperability remains challenging, limiting their applicability in sensitive domains requiring explainability. These matrices are leveraged to develop class-agnostic and class-specific tools for explainable AI of Mamba models.

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Machine Learning Explainability Neural Network Computer Vision 134

Heartbeat

JUNE 14, 2023

Introduction Deep neural network classifiers have been shown to be mis-calibrated [1], i.e., their prediction probabilities are not reliable confidence estimates. For example, if a neural network classifies an image as a “dog” with probability p , p cannot be interpreted as the confidence of the network’s predicted class for the image.

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Neural Network Computer Vision Deep Learning Explainability 59

Unite.AI

FEBRUARY 16, 2024

Despite achieving remarkable results in areas like computer vision and natural language processing , current AI systems are constrained by the quality and quantity of training data, predefined algorithms, and specific optimization objectives.

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Marktechpost

JUNE 4, 2024

Modern Deep Neural Networks (DNNs) are inherently opaque; we do not know how or why these computers arrive at the predictions they do. An emerging area of study called Explainable AI (XAI) has arisen to shed light on how DNNs make decisions in a way that humans can comprehend.

Machine Learning 113

Machine Learning Neural Network Explainability Natural Language Processing 113

Mlearning.ai

JUNE 4, 2023

Things I wish I knew before I started computer vision Python will not save you! Computer Vision is where you see the world with your eyes and explain it to a computer and make it look at the world the same way that you do. So, after some time in the field, here are some things I wish I had known.

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Marktechpost

MAY 30, 2024

Computer Vision Fundamentals with Google Cloud This course covers computer vision use cases and machine learning strategies, from using pre-built ML APIs to building custom image classifiers with linear, DNN, or CNN models. It covers how to develop NLP projects using neural networks with Vertex AI and TensorFlow.

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Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

Viso.ai

MAY 17, 2024

Neural Networks have changed the way we perform model training. With the increase in the usage of the internet and computer systems, the availability of data has become easy. Neural networks, sometimes referred to as Neural Nets, need large datasets for efficient training. What is a Liquid Neural Network?

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Neural Network Deep Learning Computer Vision Artificial Intelligence 52

Pickl AI

SEPTEMBER 5, 2024

Summary: Convolutional Neural Networks (CNNs) are essential deep learning algorithms for analysing visual data. Introduction Neural networks have revolutionised Artificial Intelligence by mimicking the human brai n’s structure to process complex data. What are Convolutional Neural Networks?

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].” What is Computer Vision?”

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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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Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

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.

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Computer Vision Neural Network Machine Learning Convolutional Neural Networks 52

Viso.ai

FEBRUARY 21, 2024

Graph Neural Networks (GNNs) are a type of neural network designed to directly operate on graphs, a data structure consisting of nodes (vertices) and edges connecting them. In this article, we’ll start with a gentle introduction to Graph Neural Networks and follow with a comprehensive technical deep dive.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

PyImageSearch

DECEMBER 9, 2024

This lesson is the last of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion NeRFs Explained: Goodbye Photogrammetry? And in the 2nd blog of this series , you were introduced to NeRFs, which is 3D Reconstruction via Neural Networks, projecting points in the 3D space.

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Computer Vision Deep Learning Explainability Algorithm 91

NVIDIA

JANUARY 17, 2024

211 DigitalPath is igniting change in the Golden State — using computer vision, generative adversarial networks and a network of thousands of cameras to detect signs of fire in real time. The AI Podcast · DigitalPath’s Ethan Higgins On Using AI to Fight Wildfires – Ep.

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Algorithm Computer Vision Neural Network AI 106

Viso.ai

DECEMBER 6, 2023

Computer vision (CV) is a rapidly evolving area in artificial intelligence (AI), allowing machines to process complex real-world visual data in different domains like healthcare, transportation, agriculture, and manufacturing. Future trends and challenges Viso Suite is an end-to-end computer vision platform.

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Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Viso.ai

MAY 14, 2024

In many computer vision applications (e.g. provides a robust end-to-end no-code computer vision solution – Viso Suite. Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks.

Computer Vision 52

Computer Vision Robotics Convolutional Neural Networks Neural Network 52

Heartbeat

AUGUST 14, 2023

Well, image segmentation in computer vision is a bit like playing a high-tech version of Tetris! So get ready to flex your Tetris skills and dive into the fascinating world of image segmentation in computer vision! Have you ever played Tetris?

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Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52

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 are artificial neural networks built to handle data having a grid-like architecture, such as photos or movies.

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The MLOps Blog

APRIL 20, 2023

With over 3 years of experience in designing, building, and deploying computer vision (CV) models , I’ve realized people don’t focus enough on crucial aspects of building and deploying such complex systems. Hopefully, at the end of this blog, you will know a bit more about finding your way around computer vision projects.

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