检索结果-内蒙古大学图书馆

Automated grading of oleaster fruit using deep learning

SCIENTIFIC REPORTS 2025年第1期15卷 1-11页

作者： Azadpour, Aram Mollazade, Kaveh Ramezani, Mohsen Samimi-Akhijahani, Hadi Univ Kurdistan Fac Agr Dept Biosyst Engn Sanandaj Iran Univ Kurdistan Fac Engn Dept Comp Engn Sanandaj Iran

The agriculture sector is crucial to many economies, particularly in developing regions, with post-harvest technology emerging as a key growth area. The oleaster, valued for its nutritional and medicinal properties, has traditionally been graded manually based on color and appearance. As global demand rises, there is a growing need for efficient automated grading methods. Therefore, this study aimed to develop a real-time machine vision system for classifying oleaster fruit at various grading velocities. Initially, in the offline phase, a dataset containing video frames of four different quality classes of oleaster, categorized based on the iranian national standard, was acquired at different linear conveyor belt velocities (ranging from 4.82 to 21.51 cm/s). The Mask R-CNN algorithm was used to segment the extracted frames to obtain the position and boundary of the samples. Experimental results indicated that, with a 100% detection rate and an average instance segmentation accuracy error ranging from 4.17 to 5.79%, the Mask R-CNN algorithm is capable of accurately segmenting all classes of oleaster at all the examined grading velocity levels. The results of the fivefold cross validation indicated that the general YOLOv8x and YOLOv8n models, created using the dataset obtained from all conveyor belt velocity levels, have a similarly reliable classification performance. Therefore, given its simpler architecture and lower processing time requirements, the YOLOv8n model was used to evaluate the grading system in real-time mode. The overall classification accuracy of this model was 92%, with a sensitivity range of 87.10-94.89% for distinguishing different classes of oleaster at a grading velocity of 21.51 cm/s. The results of this study demonstrate the effectiveness of deep learning-based models in developing grading machines for the oleaster fruit.

关键词： image segmentation Mask R-CNN Quality evaluation Real-time classification YOLOv8

来源：评论

学校读者我要写书评

暂无评论

Content-Based Retinal image Analysis: Exploring the Impact of Similarity Measures and machine Learning on LTP Features

Content-Based Retinal Image Analysis: Exploring the Impact o...

引用

2024 IEEE Students conference on Engineering and Systems, SCES 2024

作者： Santra, Arpita Singh, Vibhav Prakash Dewang, Rupesh Kumar MNNIT Allahabad Computer Science Engineering Prayagraj India

ISBN: (纸本)9798350374711

Diabetic Retinopathy (DR) is a retinal condition resulting in damage to blood vessels within the eye, serving as a leading cause of vision impairment or blindness when not addressed. Manual identification of diabetic retinopathy is labor-intensive and susceptible to human error due to the intricate nature of the eye's structure. This work offers a comprehensive method that uses image pre-processing techniques, local ternary pattern (LTP) features, machine learning and different similarity measures to improve content based retinal image analysis and retrieval from fundus images. With an emphasis on feature extraction, subtle texture details were extracted from retinal fundus images using Local Ternary Patterns (LTP) with different radius values, specifically concentrating on radius 1, 2, and 3. This study includes two parts: first, it assesses machine learning algorithms for the classification of diabetic retinopathy. Of these, Random Forest performed the best, with an accuracy of 92.77%. Second, the research works on retinal image retrieval and compares various LTP variants' abilities to different retrieval tasks. To evaluate model performance for particular disease classes, class-wise image retrieval was carried out, providing information on individual class precision. Several similarity measures were investigated for retinal image retrieval, demonstrating the effectiveness of Cosine Similarity in achieving better retrieval results. © 2024 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

vision-Based Assistive Systems for Visually Impaired People: A Review 5th

Vision-Based Assistive Systems for Visually Impaired People:...

引用

5th International conference on Optical and Wireless Technologies (OWT)

作者： Mandia, Sandeep Kumar, Ashok Verma, Karan Deegwal, Jitendra Kumar Govt Mahila Engn Coll Dept Elect & Commun Engn Ajmer 305002 India Natl Inst Technol Dept Comp Sci & Engn Delhi 110040 India Govt Engn Coll Dept Elect Instrumentat & Control Engn Ajmer 305025 India

ISBN: (纸本)9789811916458;9789811916441

This research reviews the current state of vision-based assistive solutions for the visually impaired (VI). The paper focuses primarily on camera-based assistive system solutions. We focused the review on vision-based assistive solutions proposed for VI people. The sensors, image processing algorithms, and wireless communication protocols employed in the survey have been summarised. Acoustic output devices were used in addition to cameras, Radio Frequency Identification (RFID), and Global Positioning System (GPS). vision-based assistive solutions have evolved from traditional image processing techniques to machine learning to deep learning for assistance for VI users. Wi-Fi and Bluetooth devices are the most common wireless technologies used by vision-based assistive systems. The literature does not adequately leverage the optimization of deep learning models for edge devices.

关键词： Visually impaired people vision-based assistive systems Wireless technologies

来源：评论

学校读者我要写书评

暂无评论

Digital illustration and cultural creative design of Wudang Mountain style based on graphic style transfer algorithm 3

Digital illustration and cultural creative design of Wudang ...

引用

3rd International conference on machine vision, Automatic Identification, and Detection, MVAID 2024

作者： Liu, TianYi Niu, Min Xia, Hanlong College of Art and Design Hubei University of Technology Wuhan China

ISBN: (纸本)9781510681880

In the ever-evolving landscape of computer technology and artificial intelligence, profound transformations have reverberated across the realm of art and design. This scholarly endeavor endeavors to delve into the harmonious fusion of Wudang Mountain’s venerable cultural heritage with contemporary digital art illustrations and cultural creative product designs. By meticulously scrutinizing the traditional culture of Wudang Mountain, we distill its unique cultural idiosyncrasies and artistic nuances. Employing sophisticated style transfer algorithms, we seamlessly transpose the distinctive cultural symbols and graphic elements of Wudang Mountain onto reimagined decorative motifs and visual compositions. In this symbiotic union, the essence of traditional culture is meticulously preserved, while innovative facets of modern design seamlessly interlace. This confluence not only enriches the semantic depth of digital art illustrations but also engenders a plethora of novel prospects and inspirations for cultural and creative design within scenic locales. Ultimately, this harmonious marriage of cultural innovation and technological prowess contributes to the perpetuation and elevation of Wudang Mountain’s time-honored cultural legacy, concurrently propelling the evolution of artistic expression. © 2024 SPIE.

关键词： Visualization Design image processing Feature extraction image fusion RGB color model image quality Convolutional neural networks Evolutionary algorithms Neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing Process image Analysis with Adaptive Thresholding and Deep Learning Techniques

Enhancing Process Image Analysis with Adaptive Thresholding ...

引用

2024 IEEE International conference on Imaging Systems and Techniques, IST 2024

作者： Park, Hyeong Hu Hwang, Sung Jae Kim, Do Gyun Secondary Cell Equipment Manufacturing Division Software Team APSystems Gyeonggi-do Korea Republic of

ISBN: (纸本)9798350378214

This paper presents a deep learning model specifically designed to effectively classify display Mura images. The model leverages advanced deep learning techniques and computer vision methods to identify and categorize various types of Mura based on their unique digital signatures and visual patterns. It aims to provide fast and accurate classification results, enabling real-time processing of large-scale image data. The model is expected to significantly enhance content management and user experience with display Mura, and it can be innovatively applied across various fields of image classification. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A machine Learning Approach to image Inpainting 1

引用

14th International conference on Soft Computing and Pattern Recognition, SoCPaR 2022, and the 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2022

作者： Naveenkumar, T. Kulkarni, Harsha Kulkarni, Makrand Raghavendra, H. Guru Jayashree, R. Department of CSE PES University Bengaluru India

ISBN: (数字)9783031275241

ISBN: (纸本)9783031275234

Although image inpainting, or the art of restoring old and degraded photographs/images, has been around for a long time, it has lately acquired popularity as a consequence of technical advancements in image processing technologies. Because of the developments in image processing tools and the versatility of picture editing, automatic image inpainting has become a significant and demanding subject in image processing analysis, with important applications in computer vision. The goal of this article is to develop a hybrid inpainting model that could outperform existing methods. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Polarization image processing Technology Based on machine vision Detection

Polarization Image Processing Technology Based on Machine Vi...

引用

2023 International conference on Big Data Mining and Information processing, BDMIP 2023

作者： Liu, Guoyan Zhao, Jincai Zeng, Yanan Wu, Haiyun Li, Zhi Wei, Yong College of Technology Tianjin Agricultural University Tianjin China

ISBN: (纸本)9798400709166

The detection and morphology characterization of these biological samples are the basis of life research. Optical microscopic imaging has great advantages in the characterization and detection of biological samples because of its characteristics of low sample requirements, good environmental adaptability, convenient, fast and non-destructive detection. However, due to the influence of optical diffraction limit, the resolution of optical microscopic imaging method is comparative low and thus limits the applications. Due to the polarization characteristics of the scattering field from scatterer are closely related to the microstructure of the scatterer, the measurement of the polarization characteristics of the scattering field can improve the detection and characterization ability of biological samples. Meanwhile, to achieve a higher resolution and to obtain a larger range of particle near-field scattering spectral distribution, the method in the paper takes the image acquisition part of the traditional machine vision system as the main body and a polarization modulation module is added to build an image acquisition device. The non-intuitive images obtained in the experiment are compared with the traditional direct imaging, and the results prove that the non-intuitive polarization parameter imaging can obtain the particle near-field scattering spectral distribution in a larger range than the traditional direct imaging. It is proved that non-intuitive light wave vectors are more sensitive to near-field scattering and have higher resolution. © 2023 ACM.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Semantic Preprocessor for image Compression for machines 48

Semantic Preprocessor for Image Compression for Machines

引用

48th IEEE International conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Yang, Mingyi Herranz, Luis Yang, Fei Murn, Luka Blanch, Marc Gorriz Wan, Shuai Yang, Fuzheng Mrak, Marta Xidian University School of Telecommunications Engineering Xi'an China Computer Vision Center Barcelona Spain Universitat Autònoma de Barcelona Barcelona Spain BBC Research & Development London United Kingdom Northwestern Polytechnical University School of Electronics and Information Xi'an China

ISBN: (纸本)9781728163277

Visual content is being increasingly transmitted and consumed by machines rather than humans to perform automated content analysis tasks. In this paper, we propose an image preprocessor that optimizes the input image for machine consumption prior to encoding by an off-the-shelf codec designed for human consumption. To achieve a better trade-off between the accuracy of the machine analysis task and bitrate, we propose leveraging pre-extracted semantic information to improve the preprocessor's ability to accurately identify and filter out task-irrelevant information. Furthermore, we propose a two-part loss function to optimize the preprocessor, consisted of a rate-task performance loss and a semantic distillation loss, which helps the reconstructed image obtain more information that contributes to the accuracy of the task. Experiments show that the proposed preprocessor can save up to 48.83% bitrate compared with the method without the preprocessor, and save up to 36.24% bitrate compared to existing preprocessors for machine vision. © 2023 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

3rd International conference on Artificial Intelligence and Knowledge processing, AIKP 2023

3rd International Conference on Artificial Intelligence and ...

引用

3rd International conference on Artificial Intelligence and Knowledge processing, AIKP 2023

ISBN: (纸本)9783031686160

The proceedings contain 28 papers. The special focus in this conference is on Artificial Intelligence and Knowledge processing. The topics include: How Do Senior Secondary Level Students and Their Teachers Perceive Artificial Intelligence and Its Implementation? An Exploratory Study;anomalous Sound Pattern Detection for machine Health Monitoring;performance Evaluation of Various machine Learning Algorithms for Lung Cancer Prediction Using Demographic Data;enhancing Stock Portfolio Optimization Based on a Hybrid Approach Using Artificial Bee Colony Optimization and Firefly Optimization;Enhancing Yarn Quality in the Cotton Industry: AI- Based Nep Detection for Improved Manufacturing Processes;breast Cancer Diagnosis from Ultrasonic image and Histopathology image Using Deep Learning Approach;Advancing Time Series Forecasting: LSTM Networks with Multiple Attention Mechanisms;trajectory Tracking and Navigation Model for Autonomous Vehicles Using Reinforcement Learning;quantum Graph Neural Networks Based Protein-Ligand Classification;comparative Analysis on Speech Driven Gesture Generation;enhancing Deep Learning: Leveraging Skip Connections and Memory Efficiency;quality-Based Decision-Making Using image processing for Supply Chain Management;enhancing Endometrial Tumor Detection: Early Diagnosis with Advanced vision Transformer Architecture;sweetSight: A Deep Convolutional Neural Network Approach for Automatic Categorization of Bengal Sweets;a Systematic Review: How Computer vision is Transforming Agriculture in Economic Growth;automatic Conversion of Broadcasted Football Match Recordings to Its 2D Top View;measuring the Vehicle-in-Motion, Density and Allocation of Traffic Signal Using Transfer Learning;Ensemble Model of VGG16, ResNet50, and DenseNet121 for Human Identification Through Gait Features;Performance of Sentiment Analysis APIs on Political Opinion Polling;summarization of Telugu Text Discourses;crowd-Sourced Supervisors for the Automatic Invigilation of Online

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dermatoscopic image Texture Features for Assessment of Skin Barrier 2

Dermatoscopic Image Texture Features for Assessment of Skin ...

引用

2nd International conference on image processing, Computer vision and machine Learning, ICICML 2023

作者： Chen, Yixuan He, Bingbing Lang, Xun Zhang, Ningtao Zhang, Zhao Zhang, Yufeng Yunnan University School of Information Kunming650504 China Yunnan Botanee Bio-Technology Group Co. LTD Kunming650106 China Kunming Medical University Kunming Children's Hospital Department of Dermatology Kunming650000 China

ISBN: (纸本)9798350331417

Due to the increasing prevalence of sensitive skin, it is crucial to effectively evaluate the skin barrier function. As the gold standard for assessing the skin barrier, Transepidermal Water Loss (TEWL) has been limited in its widespread use due to its high measurement costs and stringent environmental requirements. This study proposes dermatoscopic image texture features for the assessment of the sensitive skin barrier, Specifically, we extracted Gray Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP) features after pre-processing the collected dermatoscopic images, which are expected to replace TEWL. Experimental results from model mice indicate a correlation between these texture features and TEWL values, suggesting that they can be regarded as effective indicators for assessing the barrier function of sensitive skin. © 2023 IEEE.

关键词： Correlation analysis image features Skin texture TEWL

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：