2023 6th International Conference on Information and Computer Technologies (ICICT)最新文献_第4页

Deployment of Proposed EfficientNeXt on NXP i.MX 8M Mini 高效next在NXP i.MX 8M Mini上的部署

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00035

Abhishek Deokar, Mohamed El-Sharkawy

引用次数: 0

Human Tissue Cell Image Segmentation optimization Algorithm Based on Improved U-net Network 基于改进U-net网络的人体组织细胞图像分割优化算法

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00018

Jie Ying, Xin Jing, Chenyang Qin, Wei Huang

{"title":"Human Tissue Cell Image Segmentation optimization Algorithm Based on Improved U-net Network","authors":"Jie Ying, Xin Jing, Chenyang Qin, Wei Huang","doi":"10.1109/ICICT58900.2023.00018","DOIUrl":"https://doi.org/10.1109/ICICT58900.2023.00018","url":null,"abstract":"In medical testing and diagnosis, cells as the basic structure of human body, have received extensive attention in pathological research. The detection and segmentation of cells or nuclei play an important role in describing molecular morphological information. The accuracy of human tissue cells segmentation still needs to be improved, and the network segmentation results have boundary blurring and noise pixels interference. In this paper, an improved U-net network model is proposed. Aiming at the problem of simple stacking of the same convolution operation, a parallel structure for multi-scale image feature extraction is designed. Through the setting of multiple convolution operations and combining different feature fusion methods, a better convolution block structure is obtained. The network segmentation image is optimized through the secondary segmentation of Otsu method and morphological processing, and the final segmentation result is obtained. Finally, the cell contour and centroid are displayed on the original image, and the nuclear center was calculated by image moment. The experiments were carried out on the human organ H&E cell data set. The experimental results show that the Dice coefficient, Jaccard similarity coefficient, recall and accuracy of the improved U-net network model for H&E cell image segmentation reach 0.8260, 0.60, 0.8380 and 0.8270 respectively. Compared with U-net network, the above parameters of the improved U-net model are increased by 1.7%, 3.9%, 1.2% and 2.2% respectively. Compared with CNN network, the accuracy rate is improved by 3.5%, and cell segmentation is more accurate than other literatures.","PeriodicalId":425057,"journal":{"name":"2023 6th International Conference on Information and Computer Technologies (ICICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126403814","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

Design Methodology for Single-Channel CNN-Based FER Systems 基于cnn的单通道FER系统设计方法

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00022

Dorfell Parra, Carlos Camargo

{"title":"Design Methodology for Single-Channel CNN-Based FER Systems","authors":"Dorfell Parra, Carlos Camargo","doi":"10.1109/ICICT58900.2023.00022","DOIUrl":"https://doi.org/10.1109/ICICT58900.2023.00022","url":null,"abstract":"Facial Expression Recognition (FER) systems classify emotions by using geometrical approaches or Machine Learning (ML) algorithms such as Convolutional Neural Networks (CNNs). Due to their complexity, these FER systems need to be implemented on high-performance hardware, which makes them unsuitable for embedded devices. To address this challenge, we propose a methodology for the design of low-complexity, CNN-based FER systems. Our methodology includes data preprocessing, Local Binary Pattern (LBP) implementation, Data Augmentation (DA), and CNN design. Here, we also introduce the Model M6, a single-channel CNN that reaches an accuracy of 94% in less than 30 epochs. M6 has 306,182 parameters that correspond to 1.17 MB of memory. Therefore, our methodology and M6 model are feasible for implementation onto embedded systems capable of computing floating point operations. We validated our methodology and M6 model using 66 tests with 6 CNN models and 4 training parameters (batch size, learning rate, number of epochs, optimizer). This validation was performed using the Japanese Female Facial Expression (JAFFE) dataset and TensorFlow. In each test, the relationship between parameters, layers, overfitting, and underfitting was studied. Moreover, we present a step-by-step guideline on how to design the single-channel CNN and provide open-source code for readers interested in reproducing our work.","PeriodicalId":425057,"journal":{"name":"2023 6th International Conference on Information and Computer Technologies (ICICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114714747","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

An Approach to Maintain the Balance between Exploitation and Exploration of the Evolutionary Process in Multi-objective Algorithms 一种保持多目标算法中进化过程开发与探索平衡的方法

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00012

Minh Tran Binh, Long Nguyen, D. N. Duc

{"title":"An Approach to Maintain the Balance between Exploitation and Exploration of the Evolutionary Process in Multi-objective Algorithms","authors":"Minh Tran Binh, Long Nguyen, D. N. Duc","doi":"10.1109/ICICT58900.2023.00012","DOIUrl":"https://doi.org/10.1109/ICICT58900.2023.00012","url":null,"abstract":"Multi-objective optimization has been applied in many fields of science, including engineering, economics, finance, and logistics, where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives. There are several techniques to solve multi-objective optimization problems in which evolutionary algorithms are often used because they simulate the principle of natural evolution and work on population. In evolutionary algorithms, to ensure the ability to find solutions globally and quickly find the optimal solution, we must maintain the exploratory and exploitative capacities of the evolution, which also means the exploration and the exploitation of algorithms. In multi-objective optimization, population quality in diversity and convergence is essential to achieve the best possible solution set. The analysis showed that the relationship between the properties of the population directed by evolution and the ability to explore and exploit the evolutionary process is quite clear. This research evaluated the population quality according to generations of the evolutionary process based on popular measures and adjusted the algorithm to create an equilibrium transformation of those metrics, thereby better maintaining the balance between the exploration and exploitation of the population. Experiments performed on the direction-based multi-objective evolutionary algorithm with typical benchmark sets showed that the results bring good performance both in terms of solution quality and balance of the evolutionary process.","PeriodicalId":425057,"journal":{"name":"2023 6th International Conference on Information and Computer Technologies (ICICT)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131846840","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

Time-series method for predicting human traffic flow: A case study of Cañar, Ecuador 预测人类交通流量的时间序列方法:以厄瓜多尔Cañar为例

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00016

Danny Salto-Sumba, Juan Vazquez-Verdugo, Jd Jara, Jp Bermeo

{"title":"Time-series method for predicting human traffic flow: A case study of Cañar, Ecuador","authors":"Danny Salto-Sumba, Juan Vazquez-Verdugo, Jd Jara, Jp Bermeo","doi":"10.1109/ICICT58900.2023.00016","DOIUrl":"https://doi.org/10.1109/ICICT58900.2023.00016","url":null,"abstract":"The forecasts of the flow of people in urban public transport units can help governments and townships to making major decisions for efficient management of their cities, to improve their public transport service infrastructure and providing a better quality of life for their community. In this paper, we present a system that uses a traffic flow prediction model, based on neural networks, for real-time analysis of users (people) that entering to transport unit (bus) at specific stops by tagging their mobile devices. In the prediction model we perform a time correlation analysis on the data collected from the flow of people that is obtained using a WLAN network within an urban transport unit. An LSTM network model was used, this model generates an adequate performance when forecasting the number of users that could be transported. Finally, the results of this system are displayed, analyzed and stored in a WEB and SQL server, the experimental results show that our system is a solid alternative when it comes to forecasting and monitoring crowds of people in real time in transport systems.","PeriodicalId":425057,"journal":{"name":"2023 6th International Conference on Information and Computer Technologies (ICICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128682623","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

Using Artificial Intelligence to Detect Falls 使用人工智能检测跌倒

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00014

J. Sturdivant, Nicholas Morris, Tiara Hendricks, Gülüstan Dogan, Michel J. H. Heijnen

引用次数: 0

Printed Circuit Board Defect Detection Based on Improved YOLOv5 基于改进YOLOv5的印刷电路板缺陷检测

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00019

Tong Yang, Yuguo Liu, Changxin Jin, Kai Jiang, Qiang Duan, Chen Song, Qibin Chen, Xue Li, Junzheng Ge, Rui Li

{"title":"Printed Circuit Board Defect Detection Based on Improved YOLOv5","authors":"Tong Yang, Yuguo Liu, Changxin Jin, Kai Jiang, Qiang Duan, Chen Song, Qibin Chen, Xue Li, Junzheng Ge, Rui Li","doi":"10.1109/ICICT58900.2023.00019","DOIUrl":"https://doi.org/10.1109/ICICT58900.2023.00019","url":null,"abstract":"Aiming at the problems of low efficiency and poor real-time performance in the printed circuit board (PCB) defect detection, a PCB defect detection method based on the improved YOLOv5 is proposed, which integrates the module of multiscale detection, attention mechanism and multi-branch. A shallow detection layer is added to detect smaller defect targets and fused with features of the deep network. An optimized anchor clustering method was used to obtain a more suitable size for the dataset. The Convolutional Block Attention Module (CBAM) is introduced to reweight and assign important feature channels to learn more valuable features. The re-parameterization convolution (RepConv) module is integrated to decouple the multi-branch training model into a single-way inference model by structural re-parameterization, which improves the model’s training performance and reduces inference time. The experimental results show that the detection accuracy of the proposed algorithm reaches 98.3% on the extended dataset, which is 3.4% higher than that of the original algorithm. At the same time, a real-time detection performance of 63 FPS is achieved, which satisfies the detection requirements of the PCB.","PeriodicalId":425057,"journal":{"name":"2023 6th International Conference on Information and Computer Technologies (ICICT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122808665","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 Build–MaaS Architecture, a Mobility-as-a-Service platform for the Construction Sector 建筑行业移动即服务平台Build-MaaS架构的开发

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/ICICT58900.2023.00033

D. Khadraoui, C. Feltus

{"title":"Development of Build–MaaS Architecture, a Mobility-as-a-Service platform for the Construction Sector","authors":"D. Khadraoui, C. Feltus","doi":"10.1109/ICICT58900.2023.00033","DOIUrl":"https://doi.org/10.1109/ICICT58900.2023.00033","url":null,"abstract":"The demand of mobility associated with the construction sector has reached a paramount volume in the last few years, including an always more dynamically optimisation of the displacements of employees, tools and vehicles, should their be public or private. In parallel, emerging solutions arise and foster alternative approaches like the mutualization of traffic and the car–sharing. In the same spirit, multimodal mobility and Mobility as a Service (MaaS) have appear as key concepts in the professional sector with the goal to fulfill a wide number of technical and functional requirements, e.g., the delivery time and location, for each construction project, considering planning that may change depending on the evolution of the overall project. In this context, the paper introduces Build–MaaS, a specialisation of the ProMaaS platform which has been developed to open and extend existing mobility services and technologies by addressing multimodal cross-border mobility issues through the lens of the building sector. This platform aims to facilitate the mobility in the construction of the workers, their tools, and the material they need. Build–MaaS has bee identified of major interest in Luxembourg which, due to the country size, has an exceptionally high volume of business commuting needs from and to neighbouring countries, e.g. to meet partners or to visit customers.","PeriodicalId":425057,"journal":{"name":"2023 6th International Conference on Information and Computer Technologies (ICICT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123772886","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 Content-Based Dataset Recommendation System for Biomedical Datasets 基于内容的生物医学数据集推荐系统

2023 6th International Conference on Information and Computer Technologies (ICICT) Pub Date : 2023-03-01 DOI: 10.1109/icict58900.2023.00040

Zitong Zhang, Ashraf Yaseen

{"title":"A Content-Based Dataset Recommendation System for Biomedical Datasets","authors":"Zitong Zhang, Ashraf Yaseen","doi":"10.1109/icict58900.2023.00040","DOIUrl":"https://doi.org/10.1109/icict58900.2023.00040","url":null,"abstract":"Nowadays, with the rapid development of cloud data and online collaboration platforms, there is a growing trend among researchers to make their data publicly available for experimental reproducibility and data reusability. On one hand, sharing data with collaborators increases the visibility of the work. On the other hand, the abundance of data on multiple platforms makes it hard for researchers to find data relevant to their own research. To overcome this challenge, a dataset recommendation system capable of finding relevant datasets from multiple resources would be helpful. In the past two decades, few dataset recommendation methods have been implemented, that are mostly domain-specific or simply recommend datasets based on keywords. We believe a general dataset recommender system that recommends datasets with information either extracted from another dataset or supplied by researchers can enhance researchers’ efficiency in searching for relevant data and significantly improve their research efficiency. This work adopts an information retrieval (IR) paradigm for dataset recommendation. By extracting summary information from each dataset and generating a profile for each, we use and compare multiple content-based recommendation methods to recommend the most-relevant datasets in GEO, SRA, and several other repositories. Our results and evaluations prove the usefulness and need for such system.","PeriodicalId":425057,"journal":{"name":"2023 6th International Conference on Information and Computer Technologies (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115187117","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