首页 > 最新文献

International Journal of Multimedia Information Retrieval最新文献

英文 中文
Multiple feedback based adversarial collaborative filtering with aesthetics 基于美学的多重反馈对抗协同过滤
IF 5.6 3区 计算机科学 Pub Date : 2023-04-29 DOI: 10.1007/s13735-023-00273-w
Zhefu Wu, Yuhang Ma, Junzhuo Cao, Agyemang Paul, Xiang Li
{"title":"Multiple feedback based adversarial collaborative filtering with aesthetics","authors":"Zhefu Wu, Yuhang Ma, Junzhuo Cao, Agyemang Paul, Xiang Li","doi":"10.1007/s13735-023-00273-w","DOIUrl":"https://doi.org/10.1007/s13735-023-00273-w","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83123317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A deep image retrieval network using Max-m-Min pooling and morphological feature generating residual blocks 基于Max-m-Min池和形态特征生成残差块的深度图像检索网络
IF 5.6 3区 计算机科学 Pub Date : 2023-04-26 DOI: 10.1007/s13735-023-00274-9
F. Sabahi, M. Ahmad, M. Swamy
{"title":"A deep image retrieval network using Max-m-Min pooling and morphological feature generating residual blocks","authors":"F. Sabahi, M. Ahmad, M. Swamy","doi":"10.1007/s13735-023-00274-9","DOIUrl":"https://doi.org/10.1007/s13735-023-00274-9","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82688743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Study of Alzheimer’s disease brain impairment and methods for its early diagnosis: a comprehensive survey 阿尔茨海默病脑损伤及其早期诊断方法的综合研究
IF 5.6 3区 计算机科学 Pub Date : 2023-03-17 DOI: 10.1007/s13735-023-00271-y
Shruti Pallawi, D. Singh
{"title":"Study of Alzheimer’s disease brain impairment and methods for its early diagnosis: a comprehensive survey","authors":"Shruti Pallawi, D. Singh","doi":"10.1007/s13735-023-00271-y","DOIUrl":"https://doi.org/10.1007/s13735-023-00271-y","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79786611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Video anomaly detection with memory-guided multilevel embedding 基于记忆引导的多层嵌入视频异常检测
IF 5.6 3区 计算机科学 Pub Date : 2023-03-15 DOI: 10.1007/s13735-023-00272-x
Liuping Zhou, J. Yang
{"title":"Video anomaly detection with memory-guided multilevel embedding","authors":"Liuping Zhou, J. Yang","doi":"10.1007/s13735-023-00272-x","DOIUrl":"https://doi.org/10.1007/s13735-023-00272-x","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74734594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Nested-Net: a deep nested network for background subtraction 嵌套网络:用于背景减法的深度嵌套网络
IF 5.6 3区 计算机科学 Pub Date : 2023-03-07 DOI: 10.1007/s13735-023-00270-z
Fatma Gouizi, A. C. Megherbi
{"title":"Nested-Net: a deep nested network for background subtraction","authors":"Fatma Gouizi, A. C. Megherbi","doi":"10.1007/s13735-023-00270-z","DOIUrl":"https://doi.org/10.1007/s13735-023-00270-z","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80301765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
LG-MLFormer: local and global MLP for image captioning LG-MLFormer:用于图像字幕的本地和全局MLP
IF 5.6 3区 计算机科学 Pub Date : 2023-02-23 DOI: 10.1007/s13735-023-00266-9
Zetao Jiang, Xiuxian Wang, Zhongyi Zhai, Bo Cheng
{"title":"LG-MLFormer: local and global MLP for image captioning","authors":"Zetao Jiang, Xiuxian Wang, Zhongyi Zhai, Bo Cheng","doi":"10.1007/s13735-023-00266-9","DOIUrl":"https://doi.org/10.1007/s13735-023-00266-9","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79574853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Deep learning for video-text retrieval: a review 视频文本检索的深度学习:综述
IF 5.6 3区 计算机科学 Pub Date : 2023-02-23 DOI: 10.1007/s13735-023-00267-8
Cunjuan Zhu, Qi Jia, Wei Chen, Yanming Guo, Yu Liu
{"title":"Deep learning for video-text retrieval: a review","authors":"Cunjuan Zhu, Qi Jia, Wei Chen, Yanming Guo, Yu Liu","doi":"10.1007/s13735-023-00267-8","DOIUrl":"https://doi.org/10.1007/s13735-023-00267-8","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75907213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
End-to-end residual learning-based deep neural network model deployment for human activity recognition 基于端到端残差学习的人类活动识别深度神经网络模型部署
IF 5.6 3区 计算机科学 Pub Date : 2023-02-19 DOI: 10.1007/s13735-023-00269-6
Alok Negi, Krishan Kumar
{"title":"End-to-end residual learning-based deep neural network model deployment for human activity recognition","authors":"Alok Negi, Krishan Kumar","doi":"10.1007/s13735-023-00269-6","DOIUrl":"https://doi.org/10.1007/s13735-023-00269-6","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2023-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80596794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation. 情绪感知音乐塔块(EmoMTB):用于音乐发现和推荐的智能视听界面。
IF 3.6 3区 计算机科学 Pub Date : 2023-01-01 Epub Date: 2023-06-02 DOI: 10.1007/s13735-023-00275-8
Alessandro B Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Fritzl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl

Music listening has experienced a sharp increase during the last decade thanks to music streaming and recommendation services. While they offer text-based search functionality and provide recommendation lists of remarkable utility, their typical mode of interaction is unidimensional, i.e., they provide lists of consecutive tracks, which are commonly inspected in sequential order by the user. The user experience with such systems is heavily affected by cognition biases (e.g., position bias, human tendency to pay more attention to first positions of ordered lists) as well as algorithmic biases (e.g., popularity bias, the tendency of recommender systems to overrepresent popular items). This may cause dissatisfaction among the users by disabling them to find novel music to enjoy. In light of such systems and biases, we propose an intelligent audiovisual music exploration system named EmoMTB . It allows the user to browse the entirety of a given collection in a free nonlinear fashion. The navigation is assisted by a set of personalized emotion-aware recommendations, which serve as starting points for the exploration experience. EmoMTB  adopts the metaphor of a city, in which each track (visualized as a colored cube) represents one floor of a building. Highly similar tracks are located in the same building; moderately similar ones form neighborhoods that mostly correspond to genres. Tracks situated between distinct neighborhoods create a gradual transition between genres. Users can navigate this music city using their smartphones as control devices. They can explore districts of well-known music or decide to leave their comfort zone. In addition, EmoMTB   integrates an emotion-aware music recommendation system that re-ranks the list of suggested starting points for exploration according to the user's self-identified emotion or the collective emotion expressed in EmoMTB 's Twitter channel. Evaluation of EmoMTB   has been carried out in a threefold way: by quantifying the homogeneity of the clustering underlying the construction of the city, by measuring the accuracy of the emotion predictor, and by carrying out a web-based survey composed of open questions to obtain qualitative feedback from users.

在过去的十年里,由于音乐流媒体和推荐服务,音乐收听量急剧增加。虽然它们提供基于文本的搜索功能并提供非常有用的推荐列表,但它们的典型交互模式是一维的,即它们提供连续曲目的列表,用户通常按顺序检查这些曲目。这种系统的用户体验在很大程度上受到认知偏见(例如,位置偏见,人类更关注有序列表的第一位置的倾向)以及算法偏见(例如流行度偏见,推荐系统过度表达流行项目的倾向)的影响。这可能会使用户无法找到新颖的音乐来欣赏,从而引起用户的不满。鉴于这些系统和偏见,我们提出了一个名为EmoMTB的智能视听音乐探索系统。它允许用户以自由的非线性方式浏览给定集合的全部内容。导航由一组个性化的情感感知推荐来辅助,这些推荐是探索体验的起点。EmoMTB采用了城市的隐喻,其中每条轨道(可视化为彩色立方体)代表一栋建筑的一层。高度相似的轨道位于同一栋建筑内;适度相似的构成了大部分与流派相对应的邻域。位于不同街区之间的曲目创造了流派之间的逐渐过渡。用户可以使用智能手机作为控制设备在这座音乐城市中导航。他们可以探索知名音乐区,也可以决定离开自己的舒适区。此外,EmoMTB集成了一个情绪感知的音乐推荐系统,该系统根据用户的自我识别情绪或Emo山地车推特频道中表达的集体情绪,对建议的探索起点列表进行重新排序。EmoMTB的评估有三种方式:通过量化城市建设背后集群的同质性,通过测量情绪预测因子的准确性,以及通过进行由开放问题组成的网络调查,从用户那里获得定性反馈。
{"title":"Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation.","authors":"Alessandro B Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Fritzl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl","doi":"10.1007/s13735-023-00275-8","DOIUrl":"10.1007/s13735-023-00275-8","url":null,"abstract":"<p><p>Music listening has experienced a sharp increase during the last decade thanks to music streaming and recommendation services. While they offer text-based search functionality and provide recommendation lists of remarkable utility, their typical mode of interaction is unidimensional, i.e., they provide lists of consecutive tracks, which are commonly inspected in sequential order by the user. The user experience with such systems is heavily affected by cognition biases (e.g., position bias, human tendency to pay more attention to first positions of ordered lists) as well as algorithmic biases (e.g., popularity bias, the tendency of recommender systems to overrepresent popular items). This may cause dissatisfaction among the users by disabling them to find novel music to enjoy. In light of such systems and biases, we propose an intelligent audiovisual music exploration system named EmoMTB . It allows the user to browse the entirety of a given collection in a free nonlinear fashion. The navigation is assisted by a set of personalized emotion-aware recommendations, which serve as starting points for the exploration experience. EmoMTB  adopts the metaphor of a city, in which each track (visualized as a colored cube) represents one floor of a building. Highly similar tracks are located in the same building; moderately similar ones form neighborhoods that mostly correspond to genres. Tracks situated between distinct neighborhoods create a gradual transition between genres. Users can navigate this music city using their smartphones as control devices. They can explore districts of well-known music or decide to leave their comfort zone. In addition, EmoMTB   integrates an emotion-aware music recommendation system that re-ranks the list of suggested starting points for exploration according to the user's self-identified emotion or the collective emotion expressed in EmoMTB 's Twitter channel. Evaluation of EmoMTB   has been carried out in a threefold way: by quantifying the homogeneity of the clustering underlying the construction of the city, by measuring the accuracy of the emotion predictor, and by carrying out a web-based survey composed of open questions to obtain qualitative feedback from users.</p>","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9587418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Tri-RAT: optimizing the attention scores for image captioning Tri-RAT:优化图像字幕的注意分数
IF 5.6 3区 计算机科学 Pub Date : 2022-10-06 DOI: 10.1007/s13735-022-00260-7
You Yang, Yongzhi An, Juntao Hu, Longyue Pan
{"title":"Tri-RAT: optimizing the attention scores for image captioning","authors":"You Yang, Yongzhi An, Juntao Hu, Longyue Pan","doi":"10.1007/s13735-022-00260-7","DOIUrl":"https://doi.org/10.1007/s13735-022-00260-7","url":null,"abstract":"","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82612596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
期刊
International Journal of Multimedia Information Retrieval
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1