Generative adversarial networks (GANs) for image augmentation in agriculture: A systematic review

Increasing research attention has been attracted to automatic production processes in small and medium-sized enterprises (SMEs) using collaborative robotic systems. In this work, we develop an object detection solution based on deep learning on 3D point clouds for a collaborative mobile robot manipulator to automate SME production. In this solution, a 3D point cloud technology is adopted to measure the shape and depth information of targeted objects in SME production, for instance, name tags production and plug-in charging. Deep learning is then employed to deal with the uncertainty in 3D detection, such as inconsistent light conditions and the irregular distribution and structural ambiguity of point clouds. A 2D camera is employed to calibrate the relative positions of the mobile manipulator to workstations. The mobile robot manipulator is equipped with cameras, an in-house developed adaptive gripper, and a learning-based computer vision system developed in this work. The principle and procedures of the proposed 3D object detection and 2D calibration are presented in detail. The automatic name tags production and plug-in charging experiments are conducted to validate the object detection, localization algorithms, and tools developed and employed in production cases using the mobile robot manipulator.

Learning-based object detection and localization for a mobile robot manipulator in SME production

Defect detection of injection molding products on small datasets using transfer learning

Generative Adversarial Networks for Image Augmentation in Agriculture: A Systematic Review

With the development of science and technology and the progress of the times, automation and intelligence have been popularized in manufacturing in all walks of life. With the progress of productivity, product defect detection has become an indispensable part. However, in practical scenarios, the application of supervised deep learning algorithms in the field of defect detection is limited due to the difficulty and unpredictability of obtaining defect samples. In recent years, semi-supervised and unsupervised deep learning algorithms have attracted more and more attention in various defect detection tasks. Generative adversarial networks (GAN), as an unsupervised learning algorithm, has been widely used in defect detection tasks in various fields due to its powerful generation ability. In order to provide some inspiration for the researchers who intend to use GAN for defect detection research. In this paper, the theoretical basis, technical development and practical application of GAN based defect detection are reviewed. This paper also discusses the current outstanding problems of GAN and GAN-based defect detection, and makes a detailed prediction and analysis of the possible future research directions. This paper summarizes the relevant literature on the research progress and application status of GAN based defect detection, which provides certain technical information for researchers who are interested in researching GAN and hope to apply it to defect detection tasks. 

/pdf/a-survey-of-defect-detection-applications-based-on-204iuvvk.pdf

A Survey of Defect Detection Applications Based on Generative Adversarial Networks

The welding areas of the workpiece must be consistent with high precision to ensure the welding success during the welding of automobile parts. The purpose of this paper is to design an automatic high-precision locating and grasping system for robotic arm guided by 2D monocular vision to meet the requirements of automatic operation and high-precision welding.,A nonlinear multi-parallel surface calibration method based on adaptive k-segment master curve algorithm is proposed, which improves the efficiency of the traditional single camera calibration algorithm and accuracy of calibration. At the same time, the multi-dimension feature of target based on k-mean clustering constraint is proposed to improve the robustness and precision of registration.,A method of automatic locating and grasping based on 2D monocular vision is provided for robot arm, which includes camera calibration method and target locating method.,The system has been integrated into the welding robot of an automobile company in China.,A method of automatic locating and grasping based on 2D monocular vision is proposed, which makes the robot arm have automatic grasping function, and improves the efficiency and precision of automatic grasp of robot arm.

Industrial part localization and grasping using a robotic arm guided by 2D monocular vision

Quality grading of jujubes using composite convolutional neural networks in combination with RGB color space segmentation and deep convolutional generative adversarial networks

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Yu Gu

Author Tools

Chat about Author

Papers

Industrial part localization and grasping using a robotic arm guided by 2D monocular vision

Quality grading of jujubes using composite convolutional neural networks in combination with RGB color space segmentation and deep convolutional generative adversarial networks