Object Detection

A deep dive into the basic cell of many neural networks. — In this era of deep learning, where we have advanced computer vision models like YOLO, Mask RCNN, or U-Net to name a few, the foundational cell behind all of them is the Convolutional Neural Network (CNN)or to be more precise convolution operation. …

It is expected that the process of localization of industrial robots will accelerate in 2022, and the integration of industrial robots will be the key point of technological breakthroughs. 1. Review of the Industrial Robot Industry 1 Increased Robot Density The continuous improvement of the cost performance of industrial robots and the shortening of the investment recovery…

論文重點 結合region proposals與CNN，建立用於物體偵測的神經網絡。 利用supervised pre-training與domain-specific fine-tuning訓練物體偵測神經網絡模型。 原始論文：Rich feature hierarchies for accurate object detection and seman …

Abstract In this exercise we are going to use YOLOv4 object detection to detect damage/dirt on wind turbine apparatus based on images collected using drones. We will first review the concept of object detection and its difference with object classification. Then we will investigate the history of methods used in object…

Hello Everyone, This is Nivitus. Welcome to the introduction to the Object Detection blog. This is my first Computer Vision blog on a Medium site. This Computer Vision series will continue in the next upcoming blogs with various computer vision techniques. I hope all of you like this blog; ok…

Introduction Semantic segmentation is a pixel-wise classification task with many valuable applications, such as object detection and image retrieval. Despite its usefulness, semantic segmentation can be difficult to achieve good results on. …

This article will give you a simple approach (but an effective one) to code in TensorFlow that can be used recursively for any other problems in Machine Learning/Deep Learning Field. Introduction Here, we are going to talk about these topics: What is Object Recognition? Object Recognition vs Object Detection Implementation Approches …

There Are Many Challenges in Commercialization, and It Is Necessary to Use Engineering Capabilities to Break the Situation Although the needs of many industries have awakened, the commercialization of autonomous driving is still a hard nut to crack. In the stage of commercialization, the challenges we face often do not come from the autonomous driving technology itself, but from the scenarios of customers in thousands of industries, requiring…