2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)最新文献_第2页

A Review : Classification and Detection Of Plants Diseases Using Machine Learning And Soft Computing Techniques 基于机器学习和软计算技术的植物病害分类与检测研究进展

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065280

Astha Sharma, Ashwini Kumar

引用次数: 0

Classification of Chest Radiography Scans for COVID-19 COVID-19胸片扫描的分类

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064887

Navya Agarwal, Ananya Srivastava, Poonam Bansal, Kiran Malik

引用次数: 0

Analysis and Visualization of Netflix Shows Netflix节目的分析和可视化

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065331

Devashree, Himanshi Goel, N. Sharma, M. Mangla

引用次数: 0

Analysis of Cyber Attacks and Cyber Incident Patterns over APCERT Member Countries APCERT成员国的网络攻击和网络事件模式分析

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064961

Sandeep Sarowa, B. Bhanot, Vijay S. Kumar

引用次数: 0

Predicting E-learning Course Final Average-Grade using Machine Learning Techniques : A Case Study in Shaqra University 利用机器学习技术预测电子学习课程的最终平均成绩:以沙克拉大学为例

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065263

S. A. Alahmari

{"title":"Predicting E-learning Course Final Average-Grade using Machine Learning Techniques : A Case Study in Shaqra University","authors":"S. A. Alahmari","doi":"10.1109/AIST55798.2022.10065263","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10065263","url":null,"abstract":"It is critical to understand the factors that may influence students’ performance in an e-learning course delivered through a Learning Management System (LMS). The conditions affecting students are unique to every e-learning course. With wide adoption of using Machine-learning for making decisions in many areas of research. In this research, we apply machine-learning algorithms using regression analysis to predict final average grades of an e-learning course based on number of factors: total activities, total time-spent on the LMS, number of course views, and number of enrolled students. We use deep learning, decision tree, linear regression, bayesian ridge regression, and random forest techniques.The results show that the deep learning model presents the best mean absolute error, mean squared error, and R-squared for predicting the courses’ final average grade. In addition, the results reveal that the relationships between various input course features (total activities, total time-spent on the LMS, number of course views, and number of enrolled students) and the e-learning course final average grade of students is weak and required considering more features.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131440375","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

Musify: An application for Aspect Analysis and Visualization of Spotify’s song data Musify:对Spotify的歌曲数据进行方面分析和可视化的应用程序

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065226

Kanika Kamalhans, Anushka Gupta, N. Sharma, Deepak Kumar Sharma

引用次数: 0

A Survey of Morphological Analysis for Marathi Language 马拉地语词法分析综述

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065304

Sai Gokhale, Pranjali Deshpande

引用次数: 0

Artificial Intelligence in cancer survivorship care plans: what lies beyond diagnostics? 癌症生存护理计划中的人工智能:除了诊断之外还有什么?

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065173

Soumya Jindal, Meemansa Jindal, Pooja Bhati

{"title":"Artificial Intelligence in cancer survivorship care plans: what lies beyond diagnostics?","authors":"Soumya Jindal, Meemansa Jindal, Pooja Bhati","doi":"10.1109/AIST55798.2022.10065173","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10065173","url":null,"abstract":"With the worldwide rising standards of health and survival, survivorship care experiences appear to have improved significantly. However multiple barriers are causing inequities in its formulation and delivery. Artificial intelligence based digital systems can analyze and optimize multi-disciplinary teams, treatment options, communication, prognostication, and patient outcomes, besides offering unprecedented speed, accuracy, and precision. While most of the research projects are focused on AI-based detection systems, it is important to understand the scope of AI in the life of these survivors post-diagnosis. This paper provides an understanding of the existing literature and the research efforts being made toward integrating AI in cancer survivorship care after diagnosis. Method: A literature search on the PubMed database in July 2022 using keywords ((\"Artificial Intelligence\"[All Fields] OR \"Artificial Intelligence\"[MeSH Terms]) AND (\"Cancer survivorship care\"[All Fields] OR \"cancer survivor\"[MeSH Terms])) revealed 33 articles published in English. Results: Through our review we could identify three themes: ‘What are the existing loopholes in cancer survivorship care’, ‘How is AI addressing them presently’ and ‘How can AI and ML address these barriers in cancer survivorship care in the future’. We also found many loopholes in AI-assisted digital systems such as transferability, explicability, reliability, validity, data confidentiality, ownership and responsibility, noise and overdiagnosis, resources for training etc. Conclusion: In accordance with Darwin’s \"survival of the fittest\", AI-empowered clinicians, not AI will replace the traditional ones who refuse to be empowered. Recognition of the research results and the imminent need to advance will create a more equitable survivorship care delivery in the future.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130383859","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 Review For Different Sign Language Recognition Systems 不同的手语识别系统综述

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065037

Ashutosh Kumar Singh, Manik Rakhra

{"title":"A Review For Different Sign Language Recognition Systems","authors":"Ashutosh Kumar Singh, Manik Rakhra","doi":"10.1109/AIST55798.2022.10065037","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10065037","url":null,"abstract":"The fundamental aspects of communication that take place between human beings are exemplified by human language. For people who are deaf or hard of hearing, sign language is the primary mode of communication because the spoken language is inaccessible to those who are hard of hearing. As a result, many people are disabled because of hearing loss. The understanding of sign languages is a particular area of research interest. This study provides an overview and review of hand signals, gestures, and the most important methods utilised to recognise sign languages. The methods for understanding Sign Language are shown and explained. For each method, the accuracy is given. Many researchers have presented their research based on the main categories of these techniques. There are advantages and downsides, or limits associated with each technique. This study should be used as a guide to choose the best model to implement and as a road map for future research. This will help us improve the accuracy of future models and give the sign language community a better way to study how to make a fully video-based translator.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114386557","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

Handwritten Text Recognition using Deep Learning Algorithms 使用深度学习算法的手写文本识别

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065348

Arbaj Ansari, Baljinder Kaur, Manik Rakhra, Ashutosh Kumar Singh, Dalwinder Singh

{"title":"Handwritten Text Recognition using Deep Learning Algorithms","authors":"Arbaj Ansari, Baljinder Kaur, Manik Rakhra, Ashutosh Kumar Singh, Dalwinder Singh","doi":"10.1109/AIST55798.2022.10065348","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10065348","url":null,"abstract":"Since a pen is more convenient than a keyboard, most scripts are now produced by hand; this often leads to mistakes due to the illegibility of human handwriting. To combat this issue, handwriting recognition has rapidly emerged as a top research priority. Computer vision algorithms involving optical character recognition were previously employed in traditional handwriting recognition systems. It is a challenging undertaking to train an optical character recognition (OCR) system with these constraints in mind. The OCR method has many problems. In this study, we employ Convolutional Neural Networks (CNNs), Long Short-Term Memories (LSTMs) built on Recurrent Neural Network (RNN) architecture, and Connectionist Temporal Classification (CTC) to recognise handwritten text (CTC). To train and evaluate the network, we use the Information Acquisition MNIST dataset, which includes an English language handwriting test. Here, image processing is handled by OpenCV, while word recognition and training are handled by TensorFlow. Python is used throughout the development of this system, with the console serving as the final destination for the output.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115279383","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