2022 2nd Asian Conference on Innovation in Technology (ASIANCON)最新文献_第3页

A CNN-based Approach for Multi-Classification of Brain Tumors 一种基于cnn的脑肿瘤多分类方法

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9908994

Sahiti Nallamolu, Hritik Nandanwar, Anurag Singh, Subalalitha C.N.

{"title":"A CNN-based Approach for Multi-Classification of Brain Tumors","authors":"Sahiti Nallamolu, Hritik Nandanwar, Anurag Singh, Subalalitha C.N.","doi":"10.1109/ASIANCON55314.2022.9908994","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908994","url":null,"abstract":"Early diagnosis of brain tumor plays an important factor in extending the life expectancy of a patient. Therefore, an accurate and timely diagnosis of the type of brain tumor will allow adequate treatment planning and medical assistance. Radiologists commonly use magnetic resonance imaging (MRI) scans to detect and classify brain tumors. The current methods used in the medical field for diagnosis are time-consuming and prone to human error. In recent years, researchers have developed automated techniques for the segmentation and classification of MRI images resulting in a faster diagnosis process. Recent advancements in deep learning have shown greater efficiency in image recognition and classification tasks. In this paper, a convolutional neural network (CNN) (a widely used deep learning architecture for image classification tasks) is developed to classify MRI images into four brain tumor categories. Data augmentation is applied to the training dataset to generalize the images and avoid overfitting problem. Additionally, this paper compares the performance of various pre-trained models such as Vision Transformer (VIT), VGG19, ResNet50, Inception V3, and AlexNet50 with that of the proposed model. Each experiment then explores transfer learning techniques like fine-tuning and freezing layers. In the study, the proposed model yields the most efficient results with a classification accuracy of 94.72%.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133832027","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

Linguistic Severity Range Fixation of Vital Signs Using Unsupervised Approach in RHM 用无监督方法在RHM中固定生命体征的语言严重性范围

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9909372

Poorani Marimuthu

引用次数: 0

Chilli Identification and Grading in pre/post-harvest Environment based on Computer vision and Deep Learning approaches 基于计算机视觉和深度学习方法的收获前后辣椒识别与分级

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9909212

M. Sajjan, Lingangouda Kulkarni, B. Anami, N. B. Gaddagimath

{"title":"Chilli Identification and Grading in pre/post-harvest Environment based on Computer vision and Deep Learning approaches","authors":"M. Sajjan, Lingangouda Kulkarni, B. Anami, N. B. Gaddagimath","doi":"10.1109/ASIANCON55314.2022.9909212","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909212","url":null,"abstract":"Chilli, one of the spice produce, needs grading before being marketed for produce quality assurance. Manual chilli grading involves high labour cost, time-consuming, inconsistent, and expensive warranting technology intervention. In this work, a non-destructive approach to identify dry chilli images into three levels as good quality, medium quality and poor quality, using a deep learning architectures and grade them are adopted to reduce computation overload. The database of chilli grown in North Karnataka region is prepared as no standard chilli datasets are available. Dry chilli images dataset are augmented to train the dataset for transfer learning (DL) models, namely VGG16, ResNet and EfficientNet-D0 to analyse suitability of good model for the grading of chilli images. Further, work needs integration of the algorithm into automatic chilli grading tool. The proposed EfficentDet model is found suitable and yielded accuracy rate of 95.62% were in VGG16 and Resnet models accuracy was 82.67% and 83.88%. EfficientDet model out performs in terms of grading the dry chilli images.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131533467","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

Microstrip Passive Low Pass Filter (MPLPF) for Maximally Flat Response 用于最大平坦响应的微带无源低通滤波器(MPLPF)

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9908741

Aditya Prajapati, Sweta Tripathi

引用次数: 0

Microgrids and Virtual Power Plants: Integration Possibilities 微电网和虚拟电厂:整合的可能性

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9909430

L. L. Glória, S. B. Righetto, D. B. S. de Oliveira, M. A. I. Martins, R. A. S. Kraemer, M. A. Ludwig

{"title":"Microgrids and Virtual Power Plants: Integration Possibilities","authors":"L. L. Glória, S. B. Righetto, D. B. S. de Oliveira, M. A. I. Martins, R. A. S. Kraemer, M. A. Ludwig","doi":"10.1109/ASIANCON55314.2022.9909430","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909430","url":null,"abstract":"Electric power systems have undergone several transformations, especially leveraged by the trends of digitalization, decarbonization and decentralization of the electric sector. Following the trends of decarbonization and decentralization, the increased penetration of distributed resources in the electricity grid brings new challenges and opportunities for system management. In terms of digitization, the advent of microgrids and virtual power plants stands out as possibilities for aggregating and managing these resources. Thus, the integration of distributed generation, microgrids and virtual power plants presents not only new market opportunities, but also new regulatory and technological challenges for the electric system, since they change the way such entities interact with each other and with the generation, transmission, distribution and commercialization systems of electric energy, directly or indirectly impacting these sectors. In order to contribute to the discussion of topics relevant to these challenges, the present work aims to investigate possibilities for the integration of microgrids and virtual power plants. With this objective, a bibliographic mapping was carried out in order to elucidate concepts relevant to microgrids, virtual power plants and the possibilities of their integration. These themes are presented throughout the work, as well as regulatory aspects and suggestions for future research.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133503904","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

Analyzing Climate Change Dialogue During California Wildfires 分析加州野火期间的气候变化对话

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9908642

Suny Sadik, J. Benedetti, S. Gokhale

{"title":"Analyzing Climate Change Dialogue During California Wildfires","authors":"Suny Sadik, J. Benedetti, S. Gokhale","doi":"10.1109/ASIANCON55314.2022.9908642","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908642","url":null,"abstract":"This paper computationally analyzes and classifies social media dialogue on climate change based on the tweets collected and annotated during the California wildfires using a three-pronged approach. Opinions and thoughts of climate change supporters and deniers are mined through word cloud visualizations. This reveals that in the climate change debate politics and science is intertwined, with supporters stressing the imminence of climate change, and deniers deflecting it with conspiracy theories, and alternative explanations. Analysis of the metadata offers insights into how the supporting and denying tweets are being received and how they may be spread. This analysis indicates that tweets supporting climate change are shared from verified accounts, and are liked and retweeted many times, whereas those denying climate change circulate through close, like-minded communities. Sophisticated features that consider sarcasm, offensive language, emotions, and engagement are then built into a classification framework that also accounts for class imbalance. This framework can distinguish between tweets that support and deny climate change with a F1-score and accuracy of around 0.90, outperforming contemporary approaches by over 10%. By the virtue of identifying tweets that deny climate change, along with their associated justifications, the paper opens opportunities to design and disseminate educational, scientific content that can persuade the skeptics to abandon their stance.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"59 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133616244","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

Quantifying Shot Quality and Predicting the Goal Probability for Football Shots 足球射门质量量化与进球概率预测

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9909068

Shushrut Kumar, V. Jagannath, P. Visalakshi

{"title":"Quantifying Shot Quality and Predicting the Goal Probability for Football Shots","authors":"Shushrut Kumar, V. Jagannath, P. Visalakshi","doi":"10.1109/ASIANCON55314.2022.9909068","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909068","url":null,"abstract":"In the unpredictable world of football, primitive techniques are used to evaluate player performances, recruitment, and to build strategies for opponents. We aim to offer an improved and advanced technique of using predictive data like expected goals rather than descriptive data like shots taken and goals scored to analyse the game. Our goal is to judge teams and players on the basis of their performances instead of the results and generated predictive data for scouting and strategy formation. This was achieved by using fixed parameters on machine learning algorithms. The expected goals method gives a number between 0 and 1 for every shot taken, that number is interpreted as the probability of that shot being converted to goal. So if a shot at a particular location and at a certain angle produces an expected goal value off 0.67 then the probability of that shot to be a goal will be 67% meaning if 100 shots are taken from that same position and angle, 67 of those shots will result in goal and 33 shots will not be converted to goal. This method of using predictive data like expected goals is better than using primitive and orthodox descriptive data like total shots taken and shot on target ratio because this strips down the luck factor and just focuses on pure skill and ability. This will be beneficial while finding out players with real and hidden talents as well as analysing performances in an unbiased manner without the influence of final result.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128842195","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

Embedded Flexible Multi Antennas for Radio Collar IoT Applications 用于无线电项圈物联网应用的嵌入式柔性多天线

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9909335

Hemin Ismael Azeez

引用次数: 0

Improvement in Performance of Image Classification based on Apache Spark 基于Apache Spark的图像分类性能改进

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9909293

Sunil K, Sivagamasundari G

引用次数: 0

Grid-connected Hybrid Renewable Energy based Microgrid Optimization for Sustainable Energy Supply 基于并网混合可再生能源的微电网可持续能源供应优化

2022 2nd Asian Conference on Innovation in Technology (ASIANCON) Pub Date : 2022-08-26 DOI: 10.1109/ASIANCON55314.2022.9909465

Shafquat Rana, Danish Mushtaq, Nawaz Ali Warsi, M. Sarwar, A. Siddiqui

引用次数: 1