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Research and analysis of image enhancement algorithm in the classification of rock thin section images 3

Research and analysis of image enhancement algorithm in the ...

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3rd international conference on Intelligent control, Measurement and Signal Processing and Intelligent Oil Field, ICMSP 2021

作者： Huaizhou, Yang Danyang, Xu School of Computer Science Xi'An Shiyou University Xi'an China

ISBN: (纸本)9781665437158

The structure of rock flakes is complex and difficult to be classified accurately. The proposed method to solve the problem is to use an image enhancement algorithm to enhance the rock slice image. In the study, the neural network ResNet50, which has a significant effect on fine-grained classification, was used to construct the rock cast thin section image classifier, and three image enhancement algorithms, CutOut, MixUp, and CutMix, were used to enhance the rock thin section image. The rock slice images used in the data set are from Ordos, and are divided into five categories according to the size of the rock. The experimental result obtained was that the CutOut algorithm performs well on the data set, and the accuracy of the classifier was as high as 93.39%, which is 1.3% higher than the result of only using ResNet50 for classification. The experimental results show the effectiveness of the image enhancement algorithm in the classification of rock slice images. © 2021 IEEE.

关键词： Image classification

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An Extensible Framework for curricula Forecasting in Software Engineering Programs 3

An Extensible Framework for curricula Forecasting in Softwar...

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3rd international conference on Distributed Sensing and Intelligent Systems, ICDSIS 2022

作者： Alwan, Ali A. Abualkishik, Abedallah Zaid Abdullah, Radhwan M. Gulzar, Yonis School of Theoretical and Applied Science Ramapo College of New Jersey MahwahNJ United States Department of Computer Science American University in the Emirates Dubai United Arab Emirates Division of Basic Sciences University of Mosul Mosul Iraq Department of Management Information Systems King Faisal University Al-Ahsa Saudi Arabia

ISBN: (纸本)9781839538186

Universities have the responsibility to ensure that their courses prepare students with skills relevant to their future careers. As observed in many specific domains, there is often a gap between university curricula and industry needs. Such a gap is always attributed to both the remain of outdated materials and the oversight of new and relevant topics promptly due to the unavailability of a solution to keep curricula in synchronization with the continuous changes in the industry. This issue is, however, most prominent in technology-dependent disciplines, such as software engineering, where techniques, approaches, environments, and tools change continuously. While it is true that software engineering graduates will have to continuously update their knowledge during their careers, filling the skillset gap between their knowledge and the future employer's needs at the beginning of a career could be overwhelming. The aforementioned issue is a well-known problem and some common practices have been in place to resolve this issue such as bi-yearly meetings with industry board members, yearly course assessments, and individual efforts to update the course material. However, none of these provide a dynamic solution to align software engineering curricula and industry needs, maintaining such an alignment, and prompt in-time changes, as the current mechanism, often depend on the expertise and the progressive thinking of faculty. To fill this gap, this work proposes an extensible framework to proactively work in tandem with a software engineering program, serving as a "curricula forecasting" tool to support both change control and new topics/courses recommendations with longer-term visions. © IET conference proceedings 2022.

关键词： Forecasting

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Advance Machine Learning Techniques Used for Detecting and Classification of Disease in Plants: A Review 3

Advance Machine Learning Techniques Used for Detecting and C...

引用

3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Rohilla, Neeraj Rai, Munishwar Mullana M.M. Institute of Computer Technology Business Management Ambala India

ISBN: (纸本)9781665438117

Today one of the major threats for agriculture sector is the crop disease that causes big losses to the farmers. In India where maximum share of population, which is around 70% of the total, is indulged in agriculture for its livelihood. Consequently, agriculture has big role to play in Indian economy. Major concern of a farmer has always been the health of his crop. With the growth of crop plants can get viral, fungal or bacterial infection which can spread in large area of farms. To overcome and control this spread of infection farmers need expert advice so that right kind and correct amount of antibacterial, antiviral or antifungal spray can be done in farms. Earlier this process was manual but now by using various machine learning and deep learning techniques this process of detecting and classifying plant disease has been automatized. Various models have been developed by many researchers for plant disease detection and classification process. Aim of this paper is to review these models so that their potential and significance can be conveyed to agriculture sector. © 2021 IEEE.

关键词： Image segmentation

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Prediction of Pulmonary Fibrosis Progression using CNN and Regression 3

Prediction of Pulmonary Fibrosis Progression using CNN and R...

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3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Madhuri, J. Bhushan, Vikram Hr, Sai Kishore Sharan, Kumar G. Shreyas, J. Bangalore Institute of Technology Computer Science and Engineering Department Karnataka Bangalore India

ISBN: (纸本)9781665438117

The term idiopathic is used to refer to disease caused by unknown causes. Idiopathic pulmonary fibrosis is a chronic, progressive disease which affects the lungs and causes scar tissues to develop within them. This prevents the patient's lungs to transport oxygen into the bloodstream effectively. The daily routine of the patient is affected as the ease of breathing continues to decline. Early medical intervention and proper diagnosis can help keep the disease under control. The severity of the disease is measured used Forced Vital Capacity (FVC) values. In this paper we design an easy-to-use web application which collects the patient's CT scans, characteristic data and the initial FVC measurement. We predict the FVC values for up to a period of 2.5-3.0 years which effectively provides the Pulmonologist the rate of decline upon which suitable medications can be provided to stall the decline. We use Regression Techniques and CNN architectures to predict FVC values. © 2021 IEEE.

关键词： computerized tomography

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Planar yagi MIMO antenna array with improved isolation for 5.8GHz WLAN application 3

Planar yagi MIMO antenna array with improved isolation for 5...

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3rd international conference on Intelligent control, Measurement and Signal Processing and Intelligent Oil Field, ICMSP 2021

作者： Shen, Wanting Pan, Shaopeng Li, Jinxin Li, Gaosheng College of Electrical and Information Engineering Hunan University Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (纸本)9781665437158

In this paper, pattern-diversity (PD) decoupling technique is incorporated with defected ground structure (DGS) for a planar two-port Yagi multiple-input multiple-output (MIMO) antenna array. By placing two planar Yagi elements adjacent to each other symmetrically and adjusting the horizontal position of four directors, the desired pattern diversity is obtained. And etching a pair of semi-circle ring slots placed outside the two excitation dipoles into the shared ground plane, allows the isolation of more than 25 dB through the whole frequency bandwidth (5.5-6.1 GHz). The proposed MIMO antenna is manufactured on the FR-4 substrate, which is cost-effective and easy to be implemented in a MIMO system for 5.8 GHz WLAN application. © 2021 IEEE.

关键词： Defected ground structures

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Free Services - A Threat to Privacy: Ensuring a Safe Online Presence using Chrome Browser Extension 3

Free Services - A Threat to Privacy: Ensuring a Safe Online ...

引用

3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Bhadana, Krishan Panda, Supriya P. Manav Rachna International Institute of Research and Studies Faculty of Engineering and Technology Department of Computer Science Engineering Haryana Faridabad India

ISBN: (纸本)9781665438117

Internet users all across the world are concerned about the effects of free services on their privacy and security. The Internet is a vast collection of websites, the most of which are informative in nature while some are service-oriented. Paid services charge for their services, whereas others provide them for free. It may appear to be free, but there is always a catch. This paper discusses the fundamental differences between paid and free internet services, as well as the drawbacks of free services, how they can jeopardize a user's security/privacy (on occasion), and how a little bit of vigilance can shield users from prying eyes. Maintaining a balance between convenience and security goes a long way, it is understandable that removing some security walls and automating some tasks make everyday tasks easier but it is always a good habit to give preference to security. To tackle such threats, there must be a system that is looking out for user's security and privacy all the time, the system designed in this paper is a chrome browser extension that fulfills some of these tasks and ensures a better browsing experience. © 2021 IEEE.

关键词： Application programming interfaces (API)

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LCD Graphic Element Location Method Combining NL-means and Local Threshold Segmentation

LCD Graphic Element Location Method Combining NL-means and L...

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computer Technology and Information Science (ISCTIS), international Symposium on

作者： Xiaohui Wang Jianxiong Tan Shenke Technology Group Co Shijiazhuang China School of Control and Computer Engineering North China Electric Power University Baoding China

Accurate positioning of screen primitives is crucial in the machine vision-based automatic detection of intelligent water meter LCD screens. Detecting edge details of the LCD screen using the A component of the LAB color space improves the accuracy of LCD screen area positioning. This approach reduces background interference from Gaussian noise, non-uniform lighting, specular reflection, and local highlights. This study proposes a technique that combines NL-means and Sauvola local threshold segmentation methods to locate LCD screen areas and graphics elements. The experimental results indicate that this technique satisfies the defect detection criteria for smart water meter LCD screens set by the enterprise. The LCD screen detection tool extracted a smart water meter LCD screen image with 98.4% accuracy in LCD screen element positioning. Compared to the median filter method, this represents a significant improvement, and the combination with the maximum between-class variance method further increases accuracy by 2.7%.

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YOLOv8 for Product Brand Recognition as Inter-Class Similarities

YOLOv8 for Product Brand Recognition as Inter-Class Similari...

引用

Electronic and Electrical Engineering and Intelligent System (ICE3IS), international conference on

作者： Jacqueline Abyasa Marvelius Putra Kenardi Jesslyn Audrey Jonathan Jason Jovanka Christoper Justino Rissa Rahmania Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Smart retail has been increasing in interest due to societal shifts along with technological advancements. The fast-paced integration of artificial intelligence (AI) brings the opportunity to develop potential technology in the scope of daily activities. Smart retail implements a field of artificial intelligence that involves computer vision to detect and recognize products. This paper aims to analyze the performance of YOLOv8 for brand recognition on grocery products. However, the inter-class similarities problems are present among certain grocery products included in the dataset to further represent real-life conditions of smart retail. Firstly, an adequate dataset is internally developed with common grocery products from 20 classes that represent brands. In the dataset developed, 3095 images were used and split into training, validation, and testing in 70%, 20%, and 10%, respectively. Then, an experiment is conducted with the YOLOv8 model where the performance result showed by precision, recall, mean average precision (mAP), and confusion matrix. Results of the experiment show that the YOLOv8 model gives a mAP50 value of 0.96303. This result indicates that the YOLOv8 model's performance for object recognition opened new insights into its potential in supporting the automatic checkout process in smart retail.

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Design of online traffic monitoring system based on STM32 and Lora 3

Design of online traffic monitoring system based on STM32 an...

引用

3rd international conference on Intelligent control, Measurement and Signal Processing and Intelligent Oil Field, ICMSP 2021

作者： Ruirong, Dang Jianyu, Qiao Xi'An Shiyou University Shaanxi Key Laboratory of Drilling Rig Control Xi'an China

ISBN: (纸本)9781665437158

Aiming at the problem of on-line measurement of the flow of oil, gas and water multiphase flow in the production process of oil and gas wells, a set of real-time flow monitoring system based on STM32 and Lora was designed. It realizes realtime monitoring and remote control of flow, temperature and pressure in the production process of oil and gas wells. This system selects STM32F103ZET6 as the main control chip, and uses serial communication to form a data acquisition platform by connecting with sensor acquisition modules such as flow, temperature, and pressure. By using Lora wireless communication technology, real-time measurement data is transmitted to the upper computer and transmitted to Cloud Server. It is verified through the built system experiment platform that the system has the advantages of low power consumption, strong real-time performance, low cost and strong reliability. It has great production guiding significance and value for the optimization of oilfield production and the realization of intelligent well completion. © 2021 IEEE.

关键词： Data acquisition

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Automated Glaucoma Screening in Retinal Fundus Imagery: Leveraging a Convolutional Neural Network Framework

Automated Glaucoma Screening in Retinal Fundus Imagery: Leve...

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Advancement in Technology (ICONAT), international conference for

作者： Tina Babu M. Vengateshwaran K. Sasi Kala Rani Ramya Raghunath Joshi Rekha R Nair R Rajesh Sharma Department of Computer Science and Engineering Alliance University Bengaluru India Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Tamil Nadu India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

Glaucoma, a prevalent eye ailment, necessitates early detection and treatment to prevent irreversible vision loss. Conventional screening methods are often time-intensive and require specialized expertise, limiting accessibility, especially in remote areas lacking ophthalmologists. This study introduces a CNN model, harnessing deep learning to analyze retinal images and extract glaucomatous indicators. Evaluation of the CNN’s performance on a diverse dataset includes accuracy, sensitivity, specificity, and F-score assessment. Results underscore the CNN’s promise as an efficient and dependable tool for automated glaucoma screening. This advancement offers optimism for enhancing early diagnosis and intervention, critical for managing this sight-threatening condition.

关键词： Glaucoma Deep learning Training Analytical models Accuracy Transfer learning Collaboration Retina Convolutional neural networks Medical diagnostic imaging

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