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  1. DataCamp
    https://www.datacamp.com/blog/yolo-object-detection-explained

    YOLO Object Detection Explained: A Beginner's Guide

    • You Only Look Once (YOLO) is a state-of-the-art, real-time object detection algorithm introduced in 2015 by Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi in their famous researc… See more

    What Makes Yolo Popular For Object Detection?

    Some of the reasons why YOLO is leading the competition include its: 1. Speed 2. Detection accuracy 3. Good generalization 4. Open-source Let's see these features in more detail.… See more

    DataCamp
    Yolo Architecture

    YOLO architecture is similar to GoogleNet. As illustrated below, it has 24 convolutional layers, four max-pooling layers, and two fully connected layers. YOLO Architecture from the ori… See more

    DataCamp
    How Does Yolo Object Detection Work?

    Now that you understand the architecture let’s take a high-level overview of how the YOLO algorithm performs object detection using a simple use case. “Imagine you built a YOLO ap… See more

    DataCamp
    Yolo Applications

    YOLO object detection has different applications in our day-to-day life. In this section, we will cover some of them in the following domains: healthcare, agriculture, security sur… See more

    DataCamp
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    Table of Contents
    What Makes Yolo Popular For Object Detection?
    Yolo Architecture
    How Does Yolo Object Detection Work?
    Yolo Applications
    How has Yolo evolved?
     

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  2. We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to perform detection. Instead, we frame object detection as a regression problem to spatially separated bounding boxes and associated class probabilities.
    Author: Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi
    Publish Year: 2015
    Cite as: arXiv:1506.02640 [cs.CV]

    Title: You Only Look Once: Unified, Real-Time Object Detection - …

    arxiv.org/abs/1506.02640
    arxiv.org/abs/1506.02640
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  3. People also ask
    What is Yolo?
    You Only Look Once (YOLO) is a state-of-the-art, real-time object detection algorithm introduced in 2015 by Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi in their famous research paper “ You Only Look Once: Unified, Real-Time Object Detection ”.

    YOLO Object Detection Explained: A Beginner's Guide

    datacamp.com
    What is Yolo in object detection?
    We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to per-form detection. Instead, we frame object detection as a re-gression problem to spatially separated bounding boxes and associated class probabilities.

    You Only Look Once: Unified, Real-Time Object Detection

    cv-foundation.org
    How has Yolo evolved?
    YOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. We present a comprehensive analysis of YOLO’s evolution, examining the innovations and contributions in each iteration from the original YOLO up to YOLOv8, YOLO-NAS, and YOLO with Transformers.

    A Comprehensive Review of YOLO Architectures in Computer Vision: Fr…

    arxiv.org
    What is Yolo model?
    In the original YOLO model, the primary focus was on achieving high-speed object detection. The model utilized a single convolutional neural network (CNN) to directly predict object locations and classes from the input image, enabling real-time processing.

    A Comprehensive Review of YOLO: From YOLOv1 to YOLOv8 and Beyond

    arxiv.org
    What is Yolo algorithm?
    YOLO Explained. What is YOLO? | by Ani Aggarwal | Analytics Vidhya | Medium What is YOLO? YOLO or You Only Look Once, is a popular real-time object detection algorithm. YOLO combines what was once a multi-step process, using a single neural network to perform both classification and prediction of bounding boxes for detected objects.

    YOLO Explained. What is YOLO? | by Ani Aggarwal | Analytics Vidhya - …

    medium.com
    Can Yolo models expand beyond object detection and segmentation?
    YOLO models have the potential to expand beyond object detection and segmentation, exploring domains such as object tracking in videos and 3D keypoint estimation. We anticipate YOLO models to transition into multi-modal frameworks, incorporating both vision and language, video, and sound processing.

    A Comprehensive Review of YOLO Architectures in Computer Vision: Fr…

    arxiv.org
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  4. LearnOpenCV
    https://learnopencv.com/mastering-all-yol…

    Mastering All YOLO Models from YOLOv1 to …

    WEBDec 26, 2023 · However in this article, we will go through all the different versions of YOLO, from the original YOLO to YOLOv8 and YOLO-NAS, and understand their internal workings, architecture, design choices, …

     
  5. Towards Data Science
    https://towardsdatascience.com/yolo-mad…

    YOLO Made Simple: Interpreting the You Only Look …

    WEBFeb 2, 2020 · Unlike the state of the art R-CNN model, the “YOLO: Unified, Real-Time Object Detection” or “YOLOv1” presents an end-to-end …

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    • arXiv.org
      https://arxiv.org/abs/1506.02640

      Title: You Only Look Once: Unified, Real-Time Object Detection

    • arXiv.org
      https://arxiv.org/pdf/2304.00501v1
      [PDF]

      A Comprehensive Review of YOLO: From YOLOv1 to …

    • Medium
      https://medium.com/analytics-vidhya/yolo …

      YOLO Explained. What is YOLO? | by Ani Aggarwal

      WEBDec 27, 2020 · YOLO or You Only Look Once, is a popular real-time object detection algorithm. YOLO combines what was once a multi-step process, using a single neural network to perform both...

    • arXiv.org
      https://arxiv.org/html/2304.00501v6

      A Comprehensive Review of YOLO Architectures in Computer …

    • Towards Data Science
      https://towardsdatascience.com/yolo-v3-e…

      YOLO V3 Explained. In this post we’ll discuss the …

      WEBOct 9, 2020 · Inspired by ResNet and FPN (Feature-Pyramid Network) architectures, YOLO-V3 feature extractor, called Darknet-53 (it has 52 convolutions) contains skip connections (like ResNet) and 3 prediction …

    • Towards Data Science
      https://towardsdatascience.com/yolo-intuiti…

      YOLO — Intuitively and Exhaustively Explained

      WEBMay 31, 2024 · In this post we’ll discuss YOLO, the landmark paper that laid the groundwork for modern real-time computer vision. We’ll start with a brief chronology of some relevant concepts, then go through YOLO step …

    • CVF Open Access
      https://www.cv-foundation.org/openaccess/content...
      [PDF]

      You Only Look Once: Unified, Real-Time Object Detection

    • V7
      https://www.v7labs.com/blog/yolo-object-d…

      YOLO: Algorithm for Object Detection Explained …

      WEBJan 17, 2023 · What is YOLO architecture and how does it work? Learn about different YOLO algorithm versions and start training your own YOLO object detection models.

    • MDPI
      https://www.mdpi.com/2504-4990/5/4/83

      A Comprehensive Review of YOLO Architectures in Computer …

    • pjreddie.com
      https://pjreddie.com/media/files/papers/yolo.pdf
      [PDF]

      You Only Look Once: Unified, Real-Time Object Detection

    • LearnOpenCV
      https://learnopencv.com/yolov10

      YOLOv10: Paper Explanation and Inference Results - LearnOpenCV

    • Medium
      https://medium.com/hackernoon/understanding-yolo-f5a74bbc7967

      Understanding YOLO - Medium

    • Towards Data Science
      https://towardsdatascience.com/yolo-you-only-look...

      YOLO — You only look once, real time object detection explained

    • Papers With Code
      https://paperswithcode.com/method/yolov1

      YOLOv1 Explained - Papers With Code

    • ScienceDirect
      https://www.sciencedirect.com/science/article/pii/S1877050922001363

      A Review of Yolo Algorithm Developments - ScienceDirect

    • Medium
      https://medium.com/aiguys/yolo-v4-explained-in...

      YOLO v4 explained in full detail | AIGuys - Medium

    • Papers With Code
      https://paperswithcode.com/method/yolov2

      YOLOv2 Explained - Papers With Code

    • arXiv.org
      https://arxiv.org/abs/2304.00501

      [2304.00501] A Comprehensive Review of YOLO Architectures in …

    • arXiv.org
      https://arxiv.org/html/2407.02988v1

      YOLOv5, YOLOv8 and YOLOv10: The Go-To Detectors for Real …

    • arXiv.org
      https://arxiv.org/pdf/2304.00501

      arXiv.org e-Print archive