Overview of MediaEval 2020 Predicting Media Memorability task: What does it Make a Video Memorable?

This paper describes the MediaEval 2020 Predicting Media Memorability task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and long-term video memorability (VM) remains a challenging task. In 2020, the format remained the same as in previous editions. This year the videos are a subset of the TRECVid 2019 Video-to-Text dataset, containing more action rich video content as compared with the 2019 task. In this paper a description of some aspects of this task is provided, including its main characteristics, a description of the collection, the ground truth dataset, evaluation metrics and the requirements for participants’ run submissions

Overview of MediaEval 2020 predicting media memorability task: what makes a video memorable?

This paper describes the MediaEval 2020 Predicting Media Memorability task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and long-term video memorability (VM) remains a challenging task. In 2020, the format remained the same as in previous editions. This year the videos are a subset of the TRECVid 2019 Video-to-Text dataset, containing more action rich video content as compared with the 2019 task. In this paper a description of some aspects of this task is provided, including its main characteristics, a description of the collection, the ground truth dataset, evaluation metrics and the requirements for participants’ run submissions

HF-VHF帯における生体等価ファントムを用いた電磁波と人体相互作用の検証

研究科: 千葉大学大学院工学研究科学位:千大院工博甲第工185号博士(工学)千葉大

An annotated video dataset for computing video memorability

Using a collection of publicly available links to short form video clips of an average of 6 seconds duration each, 1,275 users manually annotated each video multiple times to indicate both long-term and short-term memorability of the videos. The annotations were gathered as part of an online memory game and measured a participant’s ability to recall having seen the video previously when shown a collection of videos. The recognition tasks were performed on videos seen within the previous few minutes for short-term memorability and within the previous 24 to 72 hours for long-term memorability. Data includes the reaction times for each recognition of each video. Associated with each video are text descriptions (captions) as well as a collection of image-level features applied to 3 frames extracted from each video (start, middle and end). Video-level features are also provided. The dataset was used in the Video Memorability task as part of the MediaEval benchmark in 2020

An annotated video dataset for computing video memorability

Using a collection of publicly available links to short form video clips of an average of 6 seconds duration each, 1275 users manually annotated each video multiple times to indicate both long-term and short-term memorability of the videos. The annotations were gathered as part of an online memory game and measured a participant’s ability to recall having seen the video previously when shown a collection of videos. The recognition tasks were performed on videos seen within the previous few minutes for short-term memorability and within the previous 24 to 72 hours for long-term memorability. Data includes the reaction times for each recognition of each video. Associated with each video are text descriptions (captions) as well as a collection of image-level features applied to 3 frames extracted from each video (start, middle and end). Video-level features are also provided. The dataset was used in the Video Memorability task as part of the MediaEval benchmark in 2020

Genomics in the kidney clinic

Inherited diseases are a frequent cause of end-stage kidney disease and often seen in the kidney clinic. Clinical genomic testing is increasingly available in the UK and eligible patients in England can be referred through the NHS Genomic Medicine Service. Testing is useful for diagnosis, prognostication and management of conditions such as autosomal dominant polycystic kidney disease (ADPKD), Alport syndrome, autosomal dominant tubulointerstitial kidney disease (ADTKD) and focal segmental glomerulosclerosis (FSGS). As more patients undergo genomic testing and newer technologies such as whole genome sequencing are applied, we are developing a greater appreciation of the full phenotypic spectrum of inherited kidney diseases and the challenges associated with the interpretation of clinically significant variants