AssemblyAI

MARCH 21, 2023

Introduction Graph data is everywhere in the world: any system consisting of entities and relationships between them can be represented as a graph. PinSage is able to predict in novel ways which visual concepts that users have found interesting can map to new things they might appeal to them.

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NVIDIA

JUNE 14, 2023

When California skies turned orange in the wake of devastating wildfires, a startup fused computer vision and generative AI to fight back. California utilities and fire services, they learned, were swamped with as many as 2,000 false positives a week from an existing wildfire detection system.

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Towards AI

JULY 21, 2023

Paper’s introduction Photo by Cris Ovalle on Unsplash ECCV 2020 Best Paper Award Goes to Princeton Team.They developed a new end-to-end trainable model for optical flow.Their method beats state-of-the-art architectures’ accuracy across multiple datasets and is way more efficient. They even made the code available for everyone on their Github!Let’s

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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].”

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PyImageSearch

JANUARY 2, 2023

Figure 1: Global Funding in Health Tech Companies (source: Mrazek and O’Neill, 2020 ). This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. This series is about CV and DL for Industrial and Big Business Applications.

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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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Viso.ai

DECEMBER 1, 2024

Find the applications and most popular use cases of computer vision in manufacturing. We will cover real-world applications of how manufacturing companies can use deep learning and AI vision technologies to power Computer Vision for inspection, workplace safety, factory automation, and quality control.

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Viso.ai

DECEMBER 6, 2024

Computer vision is a key component of self-driving cars. In this article, we’ll elaborate on how computer vision enhances these cars. To accomplish this, they require two key components: machine learning and computer vision. The eyes of the automobile are computer vision models.

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PyImageSearch

OCTOBER 14, 2024

Y ou may have recently heard this term via Apple and Google, or you may have seen them when studying techniques to take an image to a 3D model, when learning SLAM, or when looking at 3D Computer Vision. Neural Radiance Fields have been about turning an image into a 3D model… but using Deep Learning!

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PyImageSearch

DECEMBER 9, 2024

The next step for researchers was to use deep learning approaches such as NeRFs and 3D Gaussian Splatting, which have shown promising results in novel view synthesis, computer graphics, high-resolution image generation, and real-time rendering. Or requires a degree in computer science? Join me in computer vision mastery.

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PyImageSearch

OCTOBER 28, 2024

One day, I was looking for an email idea while writing my daily self-driving car newsletter , when I was suddenly caught by the news: Tesla had released a new FSD12 model based on End-to-End Learning. And it was because not only was the new model fully based on Deep Learning, but it also effectively removed 300,000 lines of code.

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Viso.ai

FEBRUARY 19, 2024

The evolution of computer vision technology has paved the way for innovative artificial intelligence (AI) solutions in the legal industry. Beyond traditional applications like people detection, object tracking, and behavior analysis, computer vision has the potential to offer many more creative and nuanced solutions.

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Viso.ai

OCTOBER 9, 2024

AI emotion recognition is a very active current field of computer vision research that involves facial emotion detection and the automatic assessment of sentiment from visual data and text analysis. provides the end-to-end computer vision platform Viso Suite. About us: Viso.ai

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Allen AI

JUNE 20, 2023

Allen School of Computer Science & Engineering at University of Washington, Farhadi’s research impact has been globally recognized with several best paper awards at CVPR, NeruIPS, AAAI, NSF Career Award, and the Sloan Fellowship.

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Viso.ai

JUNE 4, 2024

In many computer vision applications, engineers gather data manually. provides a robust end-to-end computer vision infrastructure – Viso Suite. Viso Suite is the only end-to-end computer vision platform What are Point Clouds? 2020) proposed a generalization of discrete CNNs. Get a demo here.

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Viso.ai

NOVEMBER 4, 2024

Power Sector Priorities to Increase Renewable Energy Production – Source Computer vision methods have great potential for gathering useful data from digital images and videos. How is Computer Vision Used in Renewables? Thus, both energy providers and customers need better short-term production, demand, and forecasting.

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Viso.ai

DECEMBER 3, 2023

This article will provide an introduction to object detection and provide an overview of the state-of-the-art computer vision object detection algorithms. Object detection is a key field in artificial intelligence, allowing computer systems to “see” their environments by detecting objects in visual images or videos.

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Heartbeat

MAY 22, 2023

Photo by Andrea Piacquadio: [link] Computer vision is one of the most widely used and evolving fields of AI. It gives the computer the ability to observe and learn from visual data just like humans. In this process, the computer derives meaningful information from digital images, videos etc.

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Towards AI

SEPTEMBER 6, 2023

From pixels to panoramas: Inside AI measuring & stitching and data-center AI powerhouse DGX GH200 AI Supercomputer (1 GPU, heavy as 4 elephants) In the realm of Computer Vision (CV), the ability to stitch together partial images and measure dimensions isn’t just an advanced trick — it’s a vital skill.

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Viso.ai

AUGUST 9, 2024

Modern Computer Vision (CV) applications are executed on the edge, i.e. directly on remote client devices. Edge computing depends on high speed and low latency to transfer large quantities of data in real-time. Moreover, applications like edge computing are necessary for 5G to sustain its expansion and coverage.

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Dlabs.ai

JUNE 19, 2020

If you Google ‘ what’s needed for deep learning ,’ you’ll find plenty of advice that says vast swathes of labeled data (say, millions of images with annotated sections) are an absolute must. You’ll probably also read that it takes a lot of computer power. in Maths; or a background in computer science, at least.

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Aiiot Talk

JANUARY 10, 2024

The project integrates deep learning AI into a next-gen microscope for real-time sample analysis displayed in augmented reality. The doctor or researcher can view the sample and analyze data without transferring the images to a computer or mailing the sample for analysis. Department of Defense.

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Towards AI

APRIL 6, 2023

Coined after the viral phrase, ‘you only live once’ (YOLO), the machine learning (ML) world first coined this acronym and repurposed it to You Only Look Once — YOLO. YOLOv1 was devised as a deep learning architecture optimized for fast object detection.

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Towards AI

APRIL 22, 2024

Ultimately, the culmination of progress in computer vision, machine learning, and biometric authentication in the 2010s has now brought FR to be a commonly integrated and adopted technology across many commercial and social applications.

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Towards AI

JULY 19, 2023

Paper’s introduction Photo by Cris Ovalle on Unsplash ECCV 2020 Best Paper Award Goes to Princeton Team.They developed a new end-to-end trainable model for optical flow.Their method beats state-of-the-art architectures’ accuracy across multiple datasets and is way more efficient. They even made the code available for everyone on their Github!Let’s

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PyImageSearch

JANUARY 22, 2024

We estimate the parameters of the generative process ( Ho, Jain, and Abbeel, “Denoising Diffusion Probabilistic Modelsm” 2020 ). 2020) The Diffusers library, developed by Hugging Face, is an accessible tool designed for a broad spectrum of deep learning practitioners. Or requires a degree in computer science?

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PyImageSearch

MAY 22, 2023

Summary Citation Information DETR Breakdown Part 1: Introduction to DEtection TRansformers In this tutorial, we’ll learn about DETR , an end-to-end trainable deep learning architecture for object detection that utilizes a transformer block. 2020) present a niche solution that transcends the old days of object detection.

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PyImageSearch

JUNE 12, 2023

2020) propose the following algorithm. Course information: 77 total classes • 96 hours of on-demand code walkthrough videos • Last updated: June 2023 ★★★★★ 4.84 (128 Ratings) • 16,000+ Students Enrolled I strongly believe that if you had the right teacher you could master computer vision and deep learning.

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Viso.ai

MAY 6, 2024

About us: Viso Suite allows machine learning teams to take control of the entire project lifecycle. By eliminating the need to purchase and manage point solutions, Viso Suite presents teams with a truly end-to-end computer vision infrastructure. To learn more, get a personalized demo from the Viso team.

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Viso.ai

OCTOBER 7, 2024

This is an iterative approach where the user interacts with a machine-learning algorithm such as a computer vision (CV) system and provides feedback on its outputs. This iterative approach involves user interaction with a machine-learning algorithm, such as a computer vision (CV) system, providing feedback on its outputs.

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Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. ViT models outperform the current state-of-the-art (CNN) by almost x4 in terms of computational efficiency and accuracy.

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How to Learn Machine Learning

MAY 14, 2023

When selecting projects, consider tackling problems in different domains, such as natural language processing, computer vision, or recommendation systems. In addition to deep learning, it’s beneficial to specialize in a specific area or technique within machine learning. Publisher) Buy on Amazon 5.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

For a given frame, our features are inspired by the 2020 Big Data Bowl Kaggle Zoo solution ( Gordeev et al. ): we construct an image for each time step with the defensive players at the rows and offensive players at the columns. Computer Vision with NFL Player Tracking Data using torch for R: Coverage classification Using CNNs.”

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Viso.ai

MAY 20, 2023

The YOLOv7 algorithm is making big waves in the computer vision and machine learning communities. provides the only end-to-end computer vision application platform, Viso Suite. The software infrastructure is used by leading organizations to gather data, train YOLOv7 models, and deliver computer vision applications.

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Viso.ai

JUNE 12, 2024

provides a robust end-to-end computer vision infrastructure – 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. About us : Viso.ai Get a demo here.

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PyImageSearch

JULY 3, 2023

Figure 2: Multi-dimensionality of Netflix recommendation system (source: Basilico, “Recent Trends in Personalization at Netflix,” NeurIPS , 2020 ). These features can be simple metadata or model-based features (extracted from a deep learning model), representing how good that video is for a member.

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AWS Machine Learning Blog

JUNE 7, 2023

Due to their size and the volume of training data they interact with, LLMs have impressive text processing abilities, including summarization, question answering, in-context learning, and more. In early 2020, research organizations across the world set the emphasis on model size, observing that accuracy correlated with number of parameters.

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