• 제목/요약/키워드: AI Video

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Real-time Camera and Video Streaming Through Optimized Settings of Ethernet AVB in Vehicle Network System

  • An, Byoungman;Kim, Youngseop
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.8
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    • pp.3025-3047
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    • 2021
  • This paper presents the latest Ethernet standardization of in-vehicle network and the future trends of automotive Ethernet technology. The proposed system provides design and optimization algorithms for automotive networking technology related to AVB (Audio Video Bridge) technology. We present a design of in-vehicle network system as well as the optimization of AVB for automotive. A proposal of Reduced Latency of Machine to Machine (RLMM) plays an outstanding role in reducing the latency among devices. RLMM's approach to real-world experimental cases indicates a reduction in latency of around 41.2%. The setup optimized for the automotive network environment is expected to significantly reduce the time in the development and design process. The results obtained in the study of image transmission latency are trustworthy because average values were collected over a long period of time. It is necessary to analyze a latency between multimedia devices within limited time which will be of considerable benefit to the industry. Furthermore, the proposed reliable camera and video streaming through optimized AVB device settings would provide a high level of support in the real-time comprehension and analysis of images with AI (Artificial Intelligence) algorithms in autonomous driving.

Separate Scale for Position Dependent Intra Prediction Combination of VVC

  • Yoon, Yong-Uk;Park, Dohyeon;Kim, Jae-Gon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.20-21
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    • 2019
  • The Joint Video Experts Team (JVET) has been working on the development of next generation of video coding standard called Versatile Video Coding (VVC). Position Dependent Intra Prediction Combination (PDPC) which is one of the major tools for intra prediction refines the prediction through a linear combination between the reconstructed samples and the predicted samples according to the sample position. In VVC WD6, nScale which is shift value that adjusts the weight is determined by the width and height of the current block. It may cause that PDPC is applied to regions that do not fit the characteristics of the current intra prediction mode. In this paper, we define nScale for each width and height so that the weight can be applied independently to the left and top reference samples, respectively. Experimental results show that, compared to VTM 6.0, the proposed method gives -0.01%, -0.04% and 0.01% Bjotegaard-Delta (BD)-rate performance, for Y, Cb, and Cr components, respectively, in All-Intra (AI) configuration.

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Comparing Zoom's Security Analysis and Security Update Results (줌의 보안 취약점 분석과 보안 업데이트 결과 비교)

  • Kim, Kyuhyeong;Choi, Younsung
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.16 no.4
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    • pp.55-65
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    • 2020
  • As corona began to spread around the world, it had such a big impact on many people's lives that the word "Untact Culture" was born. Among them, non-face-to-face meetings naturally became a daily routine as educational institutions and many domestic and foreign companies used video conferencing service platforms. Among many video conferencing service platforms, Zoom, the company with the largest number of downloads, caused many security issues and caused many concerns about Zoom's security. In this paper, Zoom's security problems and vulnerabilities were classified into five categories, and Zoom's latest update to solve those problems and the 90-day security planning project were compared and analyzed. And the problem was solved and classified as unresolved. Three of the five parts have been resolved but are still described as how they should be resolved and improved in the future for the two remaining parts.

A study on real-time internet comment system through sentiment analysis and deep learning application

  • Hae-Jong Joo;Ho-Bin Song
    • Journal of Platform Technology
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    • v.11 no.2
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    • pp.3-14
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    • 2023
  • This paper proposes a big data sentiment analysis method and deep learning implementation method to provide a webtoon comment analysis web page for convenient comment confirmation and feedback of webtoon writers for the development of the cartoon industry in the video animation field. In order to solve the difficulty of automatic analysis due to the nature of Internet comments and provide various sentiment analysis information, LSTM(Long Short-Term Memory) algorithm, ranking algorithm, and word2vec algorithm are applied in parallel, and actual popular works are used to verify the validity. If the analysis method of this paper is used, it is easy to expand to other domestic and overseas platforms, and it is expected that it can be used in various video animation content fields, not limited to the webtoon field

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CNN-Based Transformed Coefficient-Adaptive Enhancement for VVC (VVC 를 위한 CNN 기반의 변환계수 적응적 화질개선 기법)

  • Kim, Ji-Hun;Lim, Sung-Gyun;Park, Dohyeon;Kim, Jae-Gon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2021.06a
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    • pp.311-312
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    • 2021
  • 최근 VVC(Versatile Video Coding) 표준 완료 이후 JVET(Joint Video Experts Team)은 NNVC(Neural Network-based Video Coding) AhG(Ad-hoc Group)을 구성하고 인공지능을 이용한 비디오 압축 기술들을 탐색하고 있다. 본 논문에서는 VVC 복원 영상의 DCT 계수를 기반으로 복원 영상을 분류하고, 분류된 각 클래스에 따라 적응적으로 CNN(Convolutional Neural Network) 기반의 화질 개선을 수행하는 VVC 후처리 기법을 제안한다. 실험결과, 제안기법은 AI(All Intra) 부호화 모드에서 1.23% BD-rate 이득을 보였다.

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Exploring Service Improvement Opportunities through Analysis of OTT App Reviews (OTT 앱 리뷰 분석을 통한 서비스 개선 기회 발굴 방안 연구)

  • Joongmin Lee;Chie Hoon Song
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.2_2
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    • pp.445-456
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    • 2024
  • This study aims to suggest service improvement opportunities by analyzing user review data of the top three OTT service apps(Netflix, Coupang Play, and TVING) on Google Play Store. To achieve this objective, we proposed a framework for uncovering service opportunities through the analysis of negative user reviews from OTT service providers. The framework involves automating the labeling of identified topics and generating service improvement opportunities using topic modeling and prompt engineering, leveraging GPT-4, a generative AI model. Consequently, we pinpointed five dissatisfaction topics for Netflix and TVING, and nine for Coupang Play. Common issues include "video playback errors", "app installation and update errors", "subscription and payment" problems, and concerns regarding "content quality". The commonly identified service enhancement opportunities include "enhancing and diversifying content quality". "optimizing video quality and data usage", "ensuring compatibility with external devices", and "streamlining payment and cancellation processes". In contrast to prior research, this study introduces a novel research framework leveraging generative AI to label topics and propose improvement strategies based on the derived topics. This is noteworthy as it identifies actionable service opportunities aimed at enhancing service competitiveness and satisfaction, instead of merely outlining topics.

Study on Video Content Delivery Scheme for Mobile Vehicles (이동 차량을 위한 동영상 콘텐츠 전송 기법에 관한 연구)

  • Kim, Tae-Kook
    • Journal of Internet of Things and Convergence
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    • v.7 no.2
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    • pp.41-45
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    • 2021
  • This paper proposes a video content delivery scheme for vehicles. Today, we spend a lot of time commuting to work in vehicles such as trains and cars. In addition, the number of users who enjoy video content such as YouTube and Netflix in order to appease the boredom in the vehicle is increasing rapidly. Video content requires a larger amount of data usage than text-based content. Hence, the user's mobile communication data usage increases rapidly along with the cost. The proposed video content delivery scheme downloads a lot of video content in advance when the vehicle is in a free Wi-Fi area. In this way, it is possible to play video content in a vehicle at a low cost. It is expected that the proposed scheme can be applied to the Internet of Things(IoT) for moving objects.

Evaluation of Video Codec AI-based Multiple tasks (인공지능 기반 멀티태스크를 위한 비디오 코덱의 성능평가 방법)

  • Kim, Shin;Lee, Yegi;Yoon, Kyoungro;Choo, Hyon-Gon;Lim, Hanshin;Seo, Jeongil
    • Journal of Broadcast Engineering
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    • v.27 no.3
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    • pp.273-282
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    • 2022
  • MPEG-VCM(Video Coding for Machine) aims to standardize video codec for machines. VCM provides data sets and anchors, which provide reference data for comparison, for several machine vision tasks including object detection, object segmentation, and object tracking. The evaluation template can be used to compare compression and machine vision task performance between anchor data and various proposed video codecs. However, performance comparison is carried out separately for each machine vision task, and information related to performance evaluation of multiple machine vision tasks on a single bitstream is not provided currently. In this paper, we propose a performance evaluation method of a video codec for AI-based multi-tasks. Based on bits per pixel (BPP), which is the measure of a single bitstream size, and mean average precision(mAP), which is the accuracy measure of each task, we define three criteria for multi-task performance evaluation such as arithmetic average, weighted average, and harmonic average, and to calculate the multi-tasks performance results based on the mAP values. In addition, as the dynamic range of mAP may very different from task to task, performance results for multi-tasks are calculated and evaluated based on the normalized mAP in order to prevent a problem that would be happened because of the dynamic range.

Trends in Artificial Intelligence Applications in Clinical Trials: An analysis of ClinicalTrials.gov (임상시험에서 인공지능의 활용에 대한 분석 및 고찰: ClinicalTrials.gov 분석)

  • Jeong Min Go;Ji Yeon Lee;Yun-Kyoung Song;Jae Hyun Kim
    • Korean Journal of Clinical Pharmacy
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    • v.34 no.2
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    • pp.134-139
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    • 2024
  • Background: Increasing numbers of studies and research about artificial intelligence (AI) and machine learning (ML) have led to their application in clinical trials. The purpose of this study is to analyze computer-based new technologies (AI/ML) applied on clinical trials registered on ClinicalTrials.gov to elucidate current usage of these technologies. Methods: As of March 1st, 2023, protocols listed on ClinicalTrials.gov that claimed to use AI/ML and included at least one of the following interventions-Drug, Biological, Dietary Supplement, or Combination Product-were selected. The selected protocols were classified according to their context of use: 1) drug discovery; 2) toxicity prediction; 3) enrichment; 4) risk stratification/management; 5) dose selection/optimization; 6) adherence; 7) synthetic control; 8) endpoint assessment; 9) postmarketing surveillance; and 10) drug selection. Results: The applications of AI/ML were explored in 131 clinical trial protocols. The areas where AI/ML was most frequently utilized in clinical trials included endpoint assessment (n=80), followed by dose selection/optimization (n=15), risk stratification/management (n=13), drug discovery (n=4), adherence (n=4), drug selection (n=1) and enrichment (n=1). Conclusion: The most frequent application of AI/ML in clinical trials is in the fields of endpoint assessment, where the utilization is primarily focuses on the diagnosis of disease by imaging or video analyses. The number of clinical trials using artificial intelligence will increase as the technology continues to develop rapidly, making it necessary for regulatory associates to establish proper regulations for these clinical trials.

Inter-Module Interworking Evaluation of TDMA-Based Wireless IP Video Transmission System (TDMA 기반 무선 IP 영상 전송 시스템의 모듈간 연동 평가)

  • Sang-Ok Yoon;Myoung-Soo Kim;Gyeong-Hyu Seok
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.1
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    • pp.1-10
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    • 2023
  • In this paper, the design and implementation of the long-distance wireless transmission technology of high-definition video using domestic wireless communication technology for the existing wired-based CCTV surveillance system and IP camera system was evaluated for performance. The interworking test between the wireless multi-IP camera transmission terminal device and the wireless communication RF module, and the wireless multi-IP camera-based video transmission system integration interworking test confirm the module interworking suitability during video transmission.