Yolo object detection thesis

AbstractAutonomous driving will increasingly require more and more dependable network-based mechanisms, requiring redundant, real-time implementations. Object detection is a growing field of research in the field of computer vision. The ability to identify and classify objects, either in a single scene or in more than one frame, has gained huge importance in a variety of ways, as while operating a vehicle, the operator could even lack attention that could lead to disastrous collisions. YOLO is a powerful technique as it achieves high precision whilst being able to manage in real time. This paper explains the architecture and working of YOLO algorithm for the purpose of detecting and classifying objects, trained on the classes from COCO dataset.

Review: YOLOv1 — You Only Look Once (Object Detection)

YOLO Object Detection Introduction

Sign in. I was trying my hand on Optical Character Recognition on newspaper images when I realised that most documents have sections and text is not necessarily across the entire horizontal space of the page. Even though Tesseract was able to recognise the text it was jumbled up. To fix this the model should be able to identify sections on the document and draw a bounding box around it an perform OCR.

Object Detection and YOLO

Object Detection, a Computer Vision and a supervised learning task which involves predicting pixel values of each object belonging to each class. If the no. From the dataset, we can conclude that this is a mix of classification and regression. We need to predict if there is any object in the given image.
Deep Learning Object Detection Tutorials. R-CNNs are one of the first deep learning-based object detectors and are an example of a two-stage detector. The problem with the standard R-CNN method was that it was painfully slow and not a complete end-to-end object detector. Girshick et al. The Fast R-CNN algorithm made considerable improvements to the original R-CNN, namely increasing accuracy and reducing the time it took to perform a forward pass; however, the model still relied on an external region proposal algorithm.
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