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YOLO (You Only Look Once) is a state-of-the-art, real-time object detection algorithm introduced in 2015 by Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi1. YOLO frames the object detection problem as a single regression problem, rather than a classification task, by spatially separating bounding boxes and associating probabilities to each detected object using a single convolutional neural network (CNN)2.
Key Features of YOLO
Speed
YOLO is extremely fast because it processes images at 45 Frames Per Second (FPS) and can reach up to 91 FPS1. This speed is achieved by using a single forward pass through the network to make predictions, unlike other models that require multiple passes2.
High Detection Accuracy
YOLO achieves high detection accuracy with very few background errors. It generalizes well to new domains, making it suitable for applications requiring fast and robust object detection1.
Open Source
- See all on Wikipedia
You Only Look Once - Wikipedia
You Only Look Once (YOLO) is a series of real-time object detection systems based on convolutional neural networks. First introduced by Joseph Redmon et al. in 2015, YOLO has undergone several iterations and improvements, becoming one of the most popular object detection frameworks. The name "You Only … See more
Wikipedia text under CC-BY-SA license Image Recognition Algorithms: CNN, R-CNN, YOLO Explained
Feb 9, 2025 · 3. Why is YOLO faster than R-CNN-based models? YOLO processes images in a single pass, treating detection as a regression problem, while R-CNN variants use a two-stage …
Object Detection using CNN: An Introduction to the …
Jun 5, 2023 · Unlike traditional two-stage methods, YOLO performs detection in a single pass through the network, making it significantly faster. YOLO divides the input image into a grid and predicts bounding...
Faster R-CNN vs YOLO vs SSD — Object Detection …
Aug 29, 2022 · YOLO (You Only Look Once) It works solely on appearance at the image once to sight multiple objects. Thus, it’s referred to as YOLO, you merely Look Once. By simply gazing at the image once, the...
Understanding of Object Detection Based on CNN Family and …
Apr 1, 2018 · Based on the general introduction to the background and the core solution CNN, this paper exhibits one of the best CNN representatives You Only Look Once (YOLO), which …
- Author: Juan Du
- Estimated Reading Time: 1 min
- Publish Year: 2018
Object Detection with YOLO and Faster R-CNN - Medium
Nov 8, 2024 · YOLO and Faster R-CNN are prime examples of how object detection is pushing the boundaries of both speed and accuracy in deep learning. Object detection isn’t just about …
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Why YOLOv7 is better than CNN in 2024 - UBIAI
In this article, we will delve into the question of why YOLO v7, one of the latest iterations of the YOLO series, is considered superior to traditional CNNs for certain applications. We will explore the merits and capabilities of both …
YOLO Object Detection Explained: A Beginner's …
Sep 28, 2022 · The authors frame the object detection problem as a regression rather than a classification task by spatially separating bounding boxes and associating probabilities to each detected image using a single convolutional …
What Is YOLO Algorithm? | Baeldung on Computer …
Mar 18, 2024 · You Only Look Once (YOLO) is one of the most popular model architectures and object detection algorithms. It uses one of the best neural network architectures to produce high accuracy and overall processing speed, …
Comparison of Object Detection Algorithms CNN, YOLO and SSD
Nov 19, 2024 · Key methods for object detection done by “YOLO (You Only Look Once)”, “CNN”, and “SSD (Single Shot Multibox Detector)”. This paper explores three representative series of …
Object Detection with YOLO and Faster R-CNN - toxigon.com
Jan 28, 2025 · Two of the most prominent algorithms in this field are YOLO (You Only Look Once) and Faster R-CNN (Region-based Convolutional Neural Networks). In this article, we'll explore …
YOLO Explained: From v1 to v11 - viso.ai
Dec 6, 2024 · Before introducing YOLO object detection, researchers used convolutional neural network (CNN) based approaches like R-CNN and Fast R-CNN. Those approaches used a …
A Comprehensive Review of YOLO Architectures in Computer …
Techniques such as R-CNN (Region-based Convolutional Neural Networks) [1] and its successors, Fast R-CNN [2] and Faster R-CNN [3], have played a pivotal role in advancing the …
YOLO-based Object Detection Models: A Review and its …
Mar 14, 2024 · State-of-the-art models, such as YOLO and Faster R-CNN (Region-based Convolutional Neural Network), are widely employed to provide real-time and robust object …
Real Time Object Detection System with YOLO and CNN …
Jul 23, 2022 · YOU ONLY LOOK ONCE (YOLO) algorithm and it's more evolved versions are briefly described in this research survey.
What is YOLO? An In-Depth Introduction to Object Detection in
YOLO (You Only Look Once) simplifies object detection by using a single deep convolutional neural network (CNN) pass to predict bounding boxes and class probabilities. This streamlined …
R-CNN, Fast R-CNN, Faster R-CNN, YOLO - Medium
Jul 9, 2018 · Therefore, algorithms like R-CNN, YOLO etc have been developed to find these occurrences and find them fast. To bypass the problem of selecting a huge number of regions, …
YOLOv1 to YOLOv10: The fastest and most accurate real-time …
Aug 18, 2024 · Among the many real-time object detection algorithms, the YOLO (You Only Look Once) series (from v1 to v10) [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] developed in recent years is …
On-line surface defects detection of engine blocks based on …
1 day ago · Based on the above, this paper proposes an online defect detection algorithm framework based on an improved pix2pix GAN model and YOLOv5 CNN network. The U-net …
SDFC-YOLO: A YOLO-Based Model With Selective Dynamic …
5 days ago · Timely detection and treatment of road cracks are crucial to prevent further deterioration of pavement. An accurate road crack detection algorithm can significantly reduce …
YOLO does generalized object representation more effectively without precision losses than other object detection models. CNN architecture models have the ability to eliminate highlights and …
A survey: Comparison between Convolutional Neural Network …
Jan 1, 2020 · The main purpose of this paper is discussing Convolutional Neural Network (CNN) family and You Only Look Once (YOLO) family, comparing with the structure of the frame, …
YOLOv5 vs YOLOv8: A Detailed Comparison for Object Detection
Jan 8, 2025 · Its architecture is based on a single-stage detector, focusing on streamlining the detection process for rapid inference. Architecture and Key Features: Single-Stage Detector: …
An improved method of AUD-YOLO for surface damage detection …
13 hours ago · Therefore, this study proposes a WTBs damage detection model based on an improved YOLOv8, named AUD-YOLO. Firstly, the ADown module is integrated into the …