Marktechpost

MARCH 23, 2024

Deep features are pivotal in computer vision studies, unlocking image semantics and empowering researchers to tackle various tasks, even in scenarios with minimal data. With their transformative potential, deep features continue to push the boundaries of what’s possible in computer vision.

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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 110

Marktechpost

MAY 14, 2024

This article lists the top Deep Learning and Neural Networks books to help individuals gain proficiency in this vital field and contribute to its ongoing advancements and applications. Neural Networks and Deep Learning The book explores both classical and modern deep learning models, focusing on their theory and algorithms.

Neural Network 107

Neural Network Deep Learning Computer Vision Python 107

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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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.

Neural Network 122

Neural Network Explainability Machine Learning Python 122

NVIDIA

APRIL 16, 2025

Max Jaderberg, chief AI officer, and Sergei Yakneen, chief technology officer at Isomorphic Labs joined the AI Podcast to explain why they look at biology as an information processing system. Roboflow Helps Unlock Computer Vision for Every Kind of AI Builder Roboflows mission is to make the world programmable through computer vision.

Computer Vision 63

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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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Explainability Explainable AI Neural Network Algorithm 126

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 118

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?

Computer Vision 105

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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.

Machine Learning 201

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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.

Computer Vision 97

Computer Vision Robotics Deep Learning Algorithm 97

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 75

PyImageSearch

JANUARY 13, 2025

To learn how to master YOLO11 and harness its capabilities for various computer vision tasks , just keep reading. With improvements in its design and training techniques, YOLO11 can handle a variety of computer vision tasks, making it a flexible and powerful tool for developers and researchers alike.

Computer Vision 105

Computer Vision Python Deep Learning Neural Network 105

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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Marktechpost

JULY 2, 2023

Thus, there is a growing demand for explainability methods to interpret decisions made by modern machine learning models, particularly neural networks. The study was also presented at the esteemed Computer Vision and Pattern Recognition Conference, 2023, held in Canada.

Explainability 98

Explainability Neural Network AI Tools Computer Vision 98

Towards AI

JANUARY 23, 2025

Mr_oxo is looking for people to collaborate with on Computer Vision projects as accountability partners and problem-solving buddies. If youre passionate about computer vision and want to level up your skills while working on projects, connect in the thread! Meme of the week!

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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 Explainable AI Neural Network 176

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 159

Neural Network Convolutional Neural Networks BERT Deep Learning 159

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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Flipboard

DECEMBER 3, 2024

Building on years of experience in deploying ML and computer vision to address complex challenges, Syngenta introduced applications like NemaDigital, Moth Counter, and Productivity Zones. Victor Antonino , M.Eng, is a Senior Machine Learning Engineer at AWS with over a decade of experience in generative AI, computer vision, and MLOps.

Generative AI 150

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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.

Neural Network 101

Neural Network Artificial Intelligence Artificial Intelligence Natural Language Processing 101

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 77

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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Explainability Computer Vision Convolutional Neural Networks AI 184

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.

Neural Network 59

Neural Network Convolutional Neural Networks Auto-classification Deep Learning 59

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.

Neural Network 294

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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.

Neural Network 59

Neural Network Computer Vision Deep Learning Explainability 59

Unite.AI

NOVEMBER 19, 2024

NR1, combined with Qualcomm Cloud AI 100 or NVIDIA H100 or L40S GPUs, delivers a substantial performance boost over traditional CPU-centric inference servers in real-world AI applications across large language models like Llama 3, computer vision, natural language processing and speech recognition. Our solution? The NR1.

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Neural Network Natural Language Processing Python Computer Vision 157

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 114

Machine Learning Neural Network Explainability Natural Language Processing 114

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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Computer Vision Neural Network Deep Learning Python 52

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?

Neural Network 52

Neural Network Deep Learning Computer Vision Artificial Intelligence 52

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.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

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?

Convolutional Neural Networks 52

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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 135

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?”

Computer Vision 52

Computer Vision Deep Learning Neural Network Algorithm 52

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

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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Neural Network Machine Learning Algorithm Natural Language Processing 190

Marktechpost

MAY 29, 2024

This article lists the top AI courses NVIDIA provides, offering comprehensive training on advanced topics like generative AI, graph neural networks, and diffusion models, equipping learners with essential skills to excel in the field. It also covers how to set up deep learning workflows for various computer vision tasks.

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