2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)最新文献

Coral Detection using Artificial Neural Networks based on Blurry Images for Reef Protection in Cayo Blanco, Honduras 基于模糊图像的人工神经网络在洪都拉斯卡约布兰科珊瑚礁保护中的珊瑚检测

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996481

Delond Angelo Jimenez-Nixon, Jorge F. Matute Corrales, Alicia María Reyes-Duke

{"title":"Coral Detection using Artificial Neural Networks based on Blurry Images for Reef Protection in Cayo Blanco, Honduras","authors":"Delond Angelo Jimenez-Nixon, Jorge F. Matute Corrales, Alicia María Reyes-Duke","doi":"10.1109/ICMLANT56191.2022.9996481","DOIUrl":"https://doi.org/10.1109/ICMLANT56191.2022.9996481","url":null,"abstract":"Knowing the implications and benefits of coral reefs, the identification, monitoring and protection of coral species are of major importance, and applying technological advances to this process greatly adds value. Technology allows for better efficiency in terms of time, resources, personnel and the gathering of data. In Santa Fe, Honduras recently the discovered of a coral reef called Cayo Blanco was made, which is a continuation of the Mesoamerican reef. A neural network was trained using approximately 30% of blurry images. This research aims to create a graphic user interface equipped with a neural network capable of counting, classifying, and identifying at least five coral species found in Cayo Blanco, Honduras. The algorithm has 95% precision, is trained with 399 images in the Coral database, can show and register the detections, and provide a specific measurement of confidence. We concluded that for machine learning models, the quantity outperformed the quality of the image data.","PeriodicalId":224526,"journal":{"name":"2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120976826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A study of the Beeclust algorithm for robot swarm aggregation 机器人群体聚集的Beeclust算法研究

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996514

Oscar Acevedo, Y. Y. Rios, Luis García, D. Narvaez

引用次数: 0

Analyzing the Traffic of MANETs using Graph Neural Networks 基于图神经网络的manet流量分析

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996518

Taha Tekdogan

引用次数: 0

Plant Disease Detection Using DeepNets and Ensemble Technique 基于深度网络和集成技术的植物病害检测

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996468

Saanidhya Vats, Vnad Chivukula

{"title":"Plant Disease Detection Using DeepNets and Ensemble Technique","authors":"Saanidhya Vats, Vnad Chivukula","doi":"10.1109/ICMLANT56191.2022.9996468","DOIUrl":"https://doi.org/10.1109/ICMLANT56191.2022.9996468","url":null,"abstract":"Growing food security is a significant concern in the modern world. With the world's population expected to increase by two billion in the next three decades, there is a necessity to increase food production to support the growing population. In recent years, the increase in global food production has slowed, too slow to keep up with population growth. The factors directly affecting global food production are drought and plant diseases. Detection of these diseases through manual inspection is time taking and involves a factor of human error. In this paper, we focus on the problem of detecting plant diseases accurately at an early stage to increase food production. Machine learning and deep learning-based models have the potential to solve this issue by detecting plant diseases quickly and accurately. In this work, we first analyze the performance of pre-trained deep learning models on an expanded version of the standard PlantVillage dataset and then propose an ensemble of deep learning models. The proposed ensemble model outperforms all the existing deep learning models and achieves a maximum accuracy of 99.61%.","PeriodicalId":224526,"journal":{"name":"2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121570220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Systematic Review of Control Strategies for Solar Tracking Systems 太阳能跟踪系统控制策略综述

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996504

M. Cardona, Fernando E. Serrano

引用次数: 0

Effect of Complexity and Frequency of Projected Symbology of Head-Up Display while Flying in Low Visibility 低能见度飞行中平视显示器投影符号复杂度和频率的影响

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996489

Jhulan Kumar, S. Saini, Divya Agrawal, Aman Kataria, V. Karar

引用次数: 1

The Effect of Adding a One Degree of Freedom to a Robotic Manipulator 在机械臂上增加一个自由度的效果

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996535

M. Cardona, J. L. Ordoñez-Ávila, Islam Magomedouv

引用次数: 0

A Novel Monitoring System for Contagious Diseases of Patients using a Parallel Planar Robot 一种新型的基于平行平面机器人的传染病患者监测系统

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996485

J. L. Ordoñez-Ávila, M. Cardona, Douglas Adalberto Aguilar, Marcial Ordoñez, C. Garzón‐Castro

{"title":"A Novel Monitoring System for Contagious Diseases of Patients using a Parallel Planar Robot","authors":"J. L. Ordoñez-Ávila, M. Cardona, Douglas Adalberto Aguilar, Marcial Ordoñez, C. Garzón‐Castro","doi":"10.1109/ICMLANT56191.2022.9996485","DOIUrl":"https://doi.org/10.1109/ICMLANT56191.2022.9996485","url":null,"abstract":"A contagious disease can be transmitted very quickly from one person to another through direct contact or indirect contact. Today there are many doctors who become infected while monitoring their patients, this causes them to cease their work and even death. Therefore, this project has the objective of designing a robotic concept that allows remote monitoring of patients with contagious diseases, reducing direct contact between the doctor and the patient. For the design of this robot, the V methodology is proposed, which breakdown a complex prototype into a series of systems and subsystems. It is expected to obtain a robot with free obstacle locomotion applying the similarity law, thermal monitoring based on artificial vision, and facial recognition using Haar cascade. The concept was tested in solidworks motion. Finally, the proposed concept is simulated in ABS for the Housing with the capacity to withstand temperatures of up to 80 degrees Celsius and an aluminium structure with a security factor of 8.17.","PeriodicalId":224526,"journal":{"name":"2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)","volume":"42 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122741000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Implementation of Evacuation Routes with Augmented Reality in a Programmed Evacuation 基于增强现实技术的程序化疏散路线实现

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996488

M. E. Perdomo, María José Fuentes, Dennis Roberto Banegas

{"title":"Implementation of Evacuation Routes with Augmented Reality in a Programmed Evacuation","authors":"M. E. Perdomo, María José Fuentes, Dennis Roberto Banegas","doi":"10.1109/ICMLANT56191.2022.9996488","DOIUrl":"https://doi.org/10.1109/ICMLANT56191.2022.9996488","url":null,"abstract":"An AR second level-based application for general institutional evacuations was created with Unity 2020 in conjunction with Vuforia. Its function consisted of markers that serve as physical representations that mobile phones can identify to guide the user. The markers were designed with different patterns to be unique and thus be correctly recognized by the application. The objective of the implementation was to analyze the integration of RA in a scheduled general evacuation, namely, the comparison of evacuation times without application use and with application use. Based on the above, the evacuation was planned to define time, personnel, location of the markers, and time collection. Once the evacuation was completed, the statistical analysis was carried out using two sample T-tests, Dunnett's comparison, multiple regression analysis, and others. The result was that in an evacuation with many people, there was no statistical difference in the times between an evacuation with the use of the application and without the use of the application. Some of the aspects observed during the implementation that affected the evacuation time werethe processing capacity of each user's cell phone, the lighting, the trigger position, and the user's walking speed.","PeriodicalId":224526,"journal":{"name":"2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115995055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of an Artificial Vision Algorithm for T-shirt Inspection t恤检测的人工视觉算法研究

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996506

L. Serrano, M. E. Perdomo

{"title":"Development of an Artificial Vision Algorithm for T-shirt Inspection","authors":"L. Serrano, M. E. Perdomo","doi":"10.1109/ICMLANT56191.2022.9996506","DOIUrl":"https://doi.org/10.1109/ICMLANT56191.2022.9996506","url":null,"abstract":"The detection of defects in the textile industry is carried out by skilled labor to detect and classify the defects found in finished pieces. However, these personnel can make human errors that impair the quality of the final product. that is why three iterations of an artificial vision algorithm were developed for T-shirt inspection with the objective of providing the first step towards the automation of a process that has been manual for decades. This opens the door to continue automating manual operations in manufacturing workshops, to be able to implement artificial intelligence projects in the future in order to improve the efficiency of the processes and the quality of the inspections. To determine the functionality of the algorithms, experimental tests were carried out with 174 images in total. A first photo shoot was done for two colors of t-shirt: black and white; gray was also included to complete the samples and it was assumed that the slight color difference would not affect the performance of the algorithms. This first shot consisted of two batches named B1 and N1, after the initials of the colors. A second photo shoot was done in the same way with two batches named B2 and N2. Lastly, a third photo shoot was done, again with two batches called B3 and N3. An algorithm was developed for each photo shoot taken. The best method for the pictures was the 3rd one, consisting of a simple and solid background that didn't add noise to the image resulting from the algorithm. It was determined that, for white shirts, batch B2 with algorithm 2 obtained the best percentage of accuracy with a total correct detection of 31 out of the total sample of 40. For black shirts, batch N3 with algorithm 3 obtained the best percentage of accuracy with a total correct detection of 26 out of the total sample of 31.","PeriodicalId":224526,"journal":{"name":"2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129034757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1