2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)最新文献_第10页

Dense-par-AttNet: An Attention Based Deep Learning Model For Skin Lesion Classification By Transfer Learning Approach 基于迁移学习方法的皮肤病变分类深度学习模型Dense-par-AttNet

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936758

Mohammad Rakin Uddin, Talha Ibn Mahmud

{"title":"Dense-par-AttNet: An Attention Based Deep Learning Model For Skin Lesion Classification By Transfer Learning Approach","authors":"Mohammad Rakin Uddin, Talha Ibn Mahmud","doi":"10.1109/IICAIET55139.2022.9936758","DOIUrl":"https://doi.org/10.1109/IICAIET55139.2022.9936758","url":null,"abstract":"The classification of dermatoscopy images is of great significance, especially in the case of skin cancer, as the chance of survival degenerates with the passage of time. Yet, detection of a particular class of skin cancer has become a challenge in medical diagnosis due to the close resemblance among various lesions. As existing Computer-Aided Diagnosis (CAD) methods that optimize deep networks fail to perform up to the mark due to fuzzy boundaries, low contrast and limited training sets, this paper proposes a new attention-based transfer learning approach for the classification of skin lesions. In this method, pre-trained DenseNet-201 has been imported in addition to a spatial attention-based CNN network. The extracted feature of both networks are merged together to make the optimum prediction. The experimental results demonstrate the considerable performance of 82.576% overall accuracy for the HAM10000 dataset. The proposed system has a great prospective to be applied in hospitals to help dermatologists make accurate decisions in the case of skin lesion classification.","PeriodicalId":142482,"journal":{"name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132551545","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

Image Quality Assessment for Wood Images 木材图像的图像质量评估

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936864

Heshalini Rajagopal, N. Mokhtar, A. S. M. Khairuddin

引用次数: 0

A Volume and Assist Controlled Mechanical Emergency Ventilator for Respiratory Support 用于呼吸支持的容量和辅助控制机械紧急呼吸机

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936871

Asher Angelo B. Buan, Erika Faye V. Cataina, Glynn Kenneth R. Marañon, Silverio V. Magday, Angelino A. Pimentel, R. Baldovino

{"title":"A Volume and Assist Controlled Mechanical Emergency Ventilator for Respiratory Support","authors":"Asher Angelo B. Buan, Erika Faye V. Cataina, Glynn Kenneth R. Marañon, Silverio V. Magday, Angelino A. Pimentel, R. Baldovino","doi":"10.1109/IICAIET55139.2022.9936871","DOIUrl":"https://doi.org/10.1109/IICAIET55139.2022.9936871","url":null,"abstract":"Even before the COVID-19 pandemic, most hospitals in the Philippines, especially the rural and small hospitals, lacked respirators such as medical ventilators. With only a few thousand of these devices, the lack of emergency ventilators is a crucial problem in battling the COVID-19 pandemic in the Philippines. Hence, the study aimed to design an economical and portable mechanical emergency ventilator for respiratory support. It was achieved by effectively calibrating, automating, and controlling the working principle of BVM. Particularly, a CAM arm was designed to allow constant, smooth, and repeatable compression on the bag. Subsequently, driving the arm is a motor that was selected carefully according to the necessary motor torque and power calculations. Consequently, an effective close loop control system using a PID controller was implemented to control the motor position and speed. Although, the controller contains small inaccuracies that generate discrepancies in the volume measurement, and the pressure sensor records unusual readings due to breathing connection issues. The overall prototype confirms the minimum clinical specifications for a mechanical ventilator. As a result, the prototype has two ventilator modes, volume and assist control. It weighs 6.75 kg and has adimension of 385 × 270 × 235 mm.","PeriodicalId":142482,"journal":{"name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124673573","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

Health Classification System of Romaine Lettuce Plants in Hydroponic Setup Using Convolutional Neural Networks (CNN) 基于卷积神经网络的水培长叶莴苣植株健康分类系统

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936763

Jerome Martin H. Desiderio, Angelo John F. Tenorio, C. O. Manlises

{"title":"Health Classification System of Romaine Lettuce Plants in Hydroponic Setup Using Convolutional Neural Networks (CNN)","authors":"Jerome Martin H. Desiderio, Angelo John F. Tenorio, C. O. Manlises","doi":"10.1109/IICAIET55139.2022.9936763","DOIUrl":"https://doi.org/10.1109/IICAIET55139.2022.9936763","url":null,"abstract":"Hydroponics farming setup has many challenges that target the health condition of the plants, specifically romaine lettuce plants. One of the critical elements for their excellent health condition is their nutrition. Nutrients are essential components for the plant to grow, and insufficient nutrients may lead to a significant nutritional disorder that is difficult to spot during its growth stage. This may also cause marked yield and quality losses. It is also tedious to manually determine it without knowing about the plant. Plants require various ions as essential nutrients. One of the objectives of the research is to implement the convolutional neural network in determining the health condition of the leaves of the romaine lettuce. In the result of data gathering, the overall accuracy of the device in detecting and classifying leaf health is 90%. From the gathered data, the researchers have accomplished the research objectives that the proposed system can distinguish the condition of the romaine lettuce plants.","PeriodicalId":142482,"journal":{"name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127771721","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

Concurrent Architecture of High Speed Viterbi Decoder Using Xilinx HLS Tool 基于Xilinx HLS工具的高速维特比解码器并发架构

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936743

Jyoti Zunzunwala, A. S. Joshi

引用次数: 0

GPU Accelerated Metaheuristics for Integrated Production Lot Sizing and Scheduling Problems 集成生产批量和调度问题的GPU加速元启发式算法

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936782

Attilio Sbrana, Deisemara Ferreira, R. F. Cantão

引用次数: 0

Intelligent Modular Camera Rig for Classroom Lecture Video Recording System with Automatic Lighting Adjustment 一种自动调光教室讲座视频录制系统的智能模块化摄像机

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936846

Rolland Christopher C. Gamez, Gio C. Tolores, Jesus M. Martinez

{"title":"Intelligent Modular Camera Rig for Classroom Lecture Video Recording System with Automatic Lighting Adjustment","authors":"Rolland Christopher C. Gamez, Gio C. Tolores, Jesus M. Martinez","doi":"10.1109/IICAIET55139.2022.9936846","DOIUrl":"https://doi.org/10.1109/IICAIET55139.2022.9936846","url":null,"abstract":"In today's scheme where COVID-19 is the biggest problem faced by the entire world in which it almost forced all schools to suspend and obliged the students to stay at home for their safety., a video recorded lecture is one of the best solutions and ways to help students in their studies. The researchers were intended to improve distance learning as well as its effectiveness to deliver a high-quality video by developing an intelligent system that can be beneficial for both users and viewers. The usage of Arduino Uno served as the brain that controls everything, which makes the system a one-person operation. Given the scenarios of having different values of lux in a room caused by multiple kinds of events, achieving the preferred luminance will be difficult. Nevertheless, our prototype will automatically produce and attain the necessary amount of lighting needed using the LDR sensor along with the code in Arduino. The movement of the platform where the camera is placed follows wherever the user goes in front of the rig as much as the face is recognized. It was then tested using different calibrations by testing and simulating different situations where there are different variables included, such as camera movement and light. The data will be examined using ANOVA test.","PeriodicalId":142482,"journal":{"name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121721755","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

K-Zones: a Machine Learning-Based System to Estimate Social Distancing Violations During Pandemic Eras K-Zones:一个基于机器学习的系统，用于估计大流行时期违反社会距离的行为

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936803

Mohammad SaatiAlsoruji, Eihab SaatiAlsoruji

引用次数: 0

A Prototype Model of Monitoring Energy Consumption and Optimizing Distribution of Smart Buildings 智能建筑能耗监测与优化分配的原型模型

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936774

A. Shalaby, M. Sidhu, W. C. Tan, Low Zhia Wei, Chua Jing Yong, Lee Yun Xi

{"title":"A Prototype Model of Monitoring Energy Consumption and Optimizing Distribution of Smart Buildings","authors":"A. Shalaby, M. Sidhu, W. C. Tan, Low Zhia Wei, Chua Jing Yong, Lee Yun Xi","doi":"10.1109/IICAIET55139.2022.9936774","DOIUrl":"https://doi.org/10.1109/IICAIET55139.2022.9936774","url":null,"abstract":"Given the upcoming post-pandemic times, there are more universities considering adopting the hybridization model. As such, not all the facilities and building utilities will be fully utilized as only half of the student population will be expected, thus wasting the campus's energy consumption. An intelligent management system can be implemented into smart campuses to reduce the overall electrical bills to adapt to the hybrid education model. The research was then conducted on existing prior work around intelligent buildings and energy optimization. It was found that many of the energy optimization models utilized an IoT application highly specific to the designed IoT system only. This inspired developing an open source generalized IoT application to provide two-way communication between the energy optimization models and IoT devices. This would allow researchers to test their intelligent energy optimization models without building a support application from scratch. During the development phase, Firebase and open-source Chart JS were used to create an interactive web application with features including a dashboard, insightful data analysis, and remote-control features to be applied in a smart campus. A successful connection was established with a Raspberry Pi-based IoT system, where data could be stored and retrieved from the database into the web application. The second phase is going to be implementation of AI model which is currently in progress and being trained to fulfill the required criteria.","PeriodicalId":142482,"journal":{"name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117235442","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 Comparison of RGB and RGNIR Color Spaces for Plastic Waste Detection Using The YOLOv5 Architecture 基于YOLOv5结构的塑料垃圾RGB和RGNIR色彩空间检测比较

2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2022-09-13 DOI: 10.1109/IICAIET55139.2022.9936771

Owen Tamin, E. Moung, J. Dargham, Farashazillah Yahya, S. Omatu, L. Angeline

{"title":"A Comparison of RGB and RGNIR Color Spaces for Plastic Waste Detection Using The YOLOv5 Architecture","authors":"Owen Tamin, E. Moung, J. Dargham, Farashazillah Yahya, S. Omatu, L. Angeline","doi":"10.1109/IICAIET55139.2022.9936771","DOIUrl":"https://doi.org/10.1109/IICAIET55139.2022.9936771","url":null,"abstract":"Plastic waste is a serious environmental issue that damages human health, wildlife, and habitats. Many researchers have come out with multiple solutions on the problem. One of the most efficient ways is to implement machine learning approaches to detect plastic waste in common areas. Deep learning is a powerful machine learning approach that automatically learns image features for object recognition tasks using an object detector. Therefore, this paper proposed a recent object detection model, YOLOv5m, to develop a plastic waste detection model. Two plastic waste datasets, which consist of red, green, and blue (RGB) and red, green, and near-infrared (RGNIR) images, are introduced to train the proposed model. The performance of the proposed model is evaluated using 10-fold cross-validation on the two datasets. The proposed model achieves the best result on RGNIR datasets for validation and testing with an average mAP@0.5:0.95 value of 69.39% and 69.45%, respectively. These results indicate that near-infrared information can be a valuable feature representation in machine learning. This opens more possible opportunities, such as the development of automated plastic detection for the robotic and waste management industry.","PeriodicalId":142482,"journal":{"name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132660133","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