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NeRFs Explained: Goodbye Photogrammetry?

PyImageSearch

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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Photogrammetry Explained: From Multi-View Stereo to Structure from Motion

PyImageSearch

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? 3D Gaussian Splatting: The End Game of 3D Reconstruction? To learn about 3D Reconstruction, just keep reading.

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Eight Graphs that Explain Software Engineering Salaries in 2023

Flipboard

percent in 2022 compared with 2021, reflecting a steady upward trend since 2017 (with 2020 omitted due to the pandemic disruption). Tech Salaries Jump, But Don’t Keep Up With Inflation According to Dice’s numbers , tech salaries grew 2.3 However, it’s clear that the 2022 news isn’t so good when considering inflation.

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Explainability in AI and Machine Learning Systems: An Overview

Heartbeat

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

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2020 MLB Free Agency Predictions

DataRobot Blog

which indicates very strong predictive power for the 2020 offseason, assuming no major shifts in the negotiating positions of players and teams from the last decade. We believe AI is only as good as it is explainable, so the charts below show which variables our AI relied on the most to predict AAV for both pitchers and position players.

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Banking on AI: Fraud Detection, Credit Risk Analysis, and the Future of Financial Services

Unite.AI

In 2020, the financial world was rocked by a scandal involving Wirecard, a German payments processing company. One of the key challenges in AI is explainability. If a regulator questions a financial institutions’ decision made with AI, the financial institution needs to be able to explain the rationale behind it.

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Delivering responsible AI in the healthcare and life sciences industry

IBM Journey to AI blog

In 2020, the National Institute for Health (NIH) published a report stating that Black Americans died from COVID-19 at higher rates than White Americans, even though they make up a smaller percentage of the population. Mandate that outputs be auditable and explainable. And institutional innovation can play a role to help.