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GAN-Based LiDAR Intensity Simulation 基于gan的激光雷达强度模拟
News. Phi Delta Epsilon Pub Date : 2023-11-26 DOI: 10.1007/978-3-031-39059-3_28
Richard Marcus, Felix Gabel, Niklas Knoop, M. Stamminger
{"title":"GAN-Based LiDAR Intensity Simulation","authors":"Richard Marcus, Felix Gabel, Niklas Knoop, M. Stamminger","doi":"10.1007/978-3-031-39059-3_28","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_28","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"41 1","pages":"419-433"},"PeriodicalIF":0.0,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74545151","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
Improving Primate Sounds Classification using Binary Presorting for Deep Learning 基于深度学习的二值预分类改进灵长类动物声音分类
News. Phi Delta Epsilon Pub Date : 2023-06-28 DOI: 10.48550/arXiv.2306.16054
Michael Kolle, Steffen Illium, Maximilian Zorn, Jonas Nusslein, Patrick Suchostawski, Claudia Linnhoff-Popien
{"title":"Improving Primate Sounds Classification using Binary Presorting for Deep Learning","authors":"Michael Kolle, Steffen Illium, Maximilian Zorn, Jonas Nusslein, Patrick Suchostawski, Claudia Linnhoff-Popien","doi":"10.48550/arXiv.2306.16054","DOIUrl":"https://doi.org/10.48550/arXiv.2306.16054","url":null,"abstract":"In the field of wildlife observation and conservation, approaches involving machine learning on audio recordings are becoming increasingly popular. Unfortunately, available datasets from this field of research are often not optimal learning material; Samples can be weakly labeled, of different lengths or come with a poor signal-to-noise ratio. In this work, we introduce a generalized approach that first relabels subsegments of MEL spectrogram representations, to achieve higher performances on the actual multi-class classification tasks. For both the binary pre-sorting and the classification, we make use of convolutional neural networks (CNN) and various data-augmentation techniques. We showcase the results of this approach on the challenging textit{ComparE 2021} dataset, with the task of classifying between different primate species sounds, and report significantly higher Accuracy and UAR scores in contrast to comparatively equipped model baselines.","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"29 1","pages":"19-34"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86999976","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
Towards exploring adversarial learning for anomaly detection in complex driving scenes 探索对抗学习在复杂驾驶场景中的异常检测
News. Phi Delta Epsilon Pub Date : 2023-06-17 DOI: 10.48550/arXiv.2307.05256
Nouran Habib, Yunsu Cho, Abhishek Buragohain, A. Rausch
{"title":"Towards exploring adversarial learning for anomaly detection in complex driving scenes","authors":"Nouran Habib, Yunsu Cho, Abhishek Buragohain, A. Rausch","doi":"10.48550/arXiv.2307.05256","DOIUrl":"https://doi.org/10.48550/arXiv.2307.05256","url":null,"abstract":"One of the many Autonomous Systems (ASs), such as autonomous driving cars, performs various safety-critical functions. Many of these autonomous systems take advantage of Artificial Intelligence (AI) techniques to perceive their environment. But these perceiving components could not be formally verified, since, the accuracy of such AI-based components has a high dependency on the quality of training data. So Machine learning (ML) based anomaly detection, a technique to identify data that does not belong to the training data could be used as a safety measuring indicator during the development and operational time of such AI-based components. Adversarial learning, a sub-field of machine learning has proven its ability to detect anomalies in images and videos with impressive results on simple data sets. Therefore, in this work, we investigate and provide insight into the performance of such techniques on a highly complex driving scenes dataset called Berkeley DeepDrive.","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"67 1","pages":"35-55"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82852584","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 Survey on Reinforcement Learning and Deep Reinforcement Learning for Recommender Systems 推荐系统的强化学习和深度强化学习研究综述
News. Phi Delta Epsilon Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-39059-3_26
M. Rezaei, Nasseh Tabrizi
{"title":"A Survey on Reinforcement Learning and Deep Reinforcement Learning for Recommender Systems","authors":"M. Rezaei, Nasseh Tabrizi","doi":"10.1007/978-3-031-39059-3_26","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_26","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"108 1","pages":"385-402"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77435558","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
Research Data Reusability with Content-Based Recommender System 基于内容的推荐系统研究数据可重用性
News. Phi Delta Epsilon Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-39059-3_10
M. A. Yazdi, Marius Politze, Benedikt Heinrichs
{"title":"Research Data Reusability with Content-Based Recommender System","authors":"M. A. Yazdi, Marius Politze, Benedikt Heinrichs","doi":"10.1007/978-3-031-39059-3_10","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_10","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"46 1","pages":"143-156"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80897284","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
TaxoSBERT: Unsupervised Taxonomy Expansion Through Expressive Semantic Similarity TaxoSBERT:基于表达语义相似性的无监督分类法扩展
News. Phi Delta Epsilon Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-39059-3_20
Daniele Margiotta, D. Croce, Roberto Basili
{"title":"TaxoSBERT: Unsupervised Taxonomy Expansion Through Expressive Semantic Similarity","authors":"Daniele Margiotta, D. Croce, Roberto Basili","doi":"10.1007/978-3-031-39059-3_20","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_20","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"32 1","pages":"295-307"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87493833","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
Dynamic Prediction of Survival Status in Patients Undergoing Cardiac Catheterization Using a Joint Modeling Approach 使用关节建模方法动态预测心导管置入术患者的生存状态
News. Phi Delta Epsilon Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-39059-3_4
Derun Xia, Y. Ko, Shivang R. Desai, A. Quyyumi
{"title":"Dynamic Prediction of Survival Status in Patients Undergoing Cardiac Catheterization Using a Joint Modeling Approach","authors":"Derun Xia, Y. Ko, Shivang R. Desai, A. Quyyumi","doi":"10.1007/978-3-031-39059-3_4","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_4","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"13 1","pages":"56-70"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87774444","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 Automated Dual-Module Pipeline for Stock Prediction: Integrating N-Perception Period Power Strategy and NLP-Driven Sentiment Analysis for Enhanced Forecasting Accuracy and Investor Insight 股票预测的自动化双模块管道:整合n感知周期功率策略和nlp驱动的情绪分析，以提高预测准确性和投资者洞察力
News. Phi Delta Epsilon Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-39059-3_6
Siddhant Singh, Archit Thanikella
{"title":"An Automated Dual-Module Pipeline for Stock Prediction: Integrating N-Perception Period Power Strategy and NLP-Driven Sentiment Analysis for Enhanced Forecasting Accuracy and Investor Insight","authors":"Siddhant Singh, Archit Thanikella","doi":"10.1007/978-3-031-39059-3_6","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_6","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"24 1","pages":"84-100"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82985383","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
GAN-Powered Model &Landmark-Free Reconstruction: A Versatile Approach for High-Quality 3D Facial and Object Recovery from Single Images 氮化镓驱动的模型和无地标重建:从单个图像中恢复高质量3D面部和物体的通用方法
News. Phi Delta Epsilon Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-39059-3_27
Michael Danner, P. Huber, Muhammad Awais, Matthias Rätsch, J. Kittler
{"title":"GAN-Powered Model &Landmark-Free Reconstruction: A Versatile Approach for High-Quality 3D Facial and Object Recovery from Single Images","authors":"Michael Danner, P. Huber, Muhammad Awais, Matthias Rätsch, J. Kittler","doi":"10.1007/978-3-031-39059-3_27","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_27","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"27 1","pages":"403-418"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81529910","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
Generative Adversarial Networks for Domain Translation in Unpaired Breast DCE-MRI Datasets 非配对乳腺DCE-MRI数据集领域翻译的生成对抗网络
News. Phi Delta Epsilon Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-39059-3_25
Antonio Galli, M. Gravina, S. Marrone, Carlo Sansone
{"title":"Generative Adversarial Networks for Domain Translation in Unpaired Breast DCE-MRI Datasets","authors":"Antonio Galli, M. Gravina, S. Marrone, Carlo Sansone","doi":"10.1007/978-3-031-39059-3_25","DOIUrl":"https://doi.org/10.1007/978-3-031-39059-3_25","url":null,"abstract":"","PeriodicalId":88612,"journal":{"name":"News. Phi Delta Epsilon","volume":"11 1","pages":"370-384"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74291899","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
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