scholarly journals Research on the Influence of New Media Technology on Internet Short Video Content Production under Artificial Intelligence Background

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhiqin Lu ◽  
Inyong Nam
Keyword(s):  
Artificial Intelligence ◽  
New Media ◽  
Large Scale ◽  
Rapid Development ◽  
Smart Phone ◽  
Video Content ◽  
Video Content Analysis ◽  
Short Video ◽  
Popular Work ◽  
Basic Features

With the rapid development of the Internet and smart phone technology, a large number of short videos are shared through social platforms. Therefore, video content analysis is a very important and popular work in machine learning and artificial intelligence currently. However, it is very difficult to analyze all aspects of video content originally produced by large-scale users. How to screen out bad and illegal content from short videos published by a large number of users, select high-quality videos to share with other users, and improve the quality of video on the distribution platform of the entire user is a top priority. Based on this background, this paper focuses on optimizing video auditing to provide basic features for algorithm judgment, supporting original content and increasing the distribution of new content, and strengthening manual intervention combining algorithm recommendation with manual recommendation. Four major aspects of the artificial training algorithm model discuss the optimization effect of artificial intelligence on the algorithm in order to provide some guidance for the sustainable and healthy development of mobile short video.

scholarly journals User-generated news: Netizen journalism in China in the age of short video

2019 ◽  
Vol 4 (1) ◽  
pp. 52-71 ◽  
Author(s):  
Yu Xiang
Keyword(s):  
New Media ◽  
Rapid Development ◽  
User Generated Content ◽  
Media Technology ◽  
Xinhua News Agency ◽  
The World ◽  
Social Media Platforms ◽  
Short Video ◽  
Use Of Social Media ◽  
The Many

As media technology advances, and with increasingly rapid development, there has been an unprecedented growth in the number of new media platforms emerging in China—and throughout the world—that are changing the procedures of how news is assembled and disseminated by effectively and efficiently adopting user-generated content that has injected new blood into the very nature of journalism. While essentially this is encouraging the productive use of social media platforms, it is also having an impact on users, transforming vast numbers into what are now recognized as “netizen journalists.” This leads us to inquire just how the journalistic outputs of short video platforms of such media outfits like Pear Video and Kwai are framed and also to explore how the roles of the “ordinary” users of such platforms are now defined by their participation in the actual production of news and information. This research aims to contribute to the many discussions on the above questions based on the journalistic study on three different news platforms: Xinhua News Agency’ as adopted and adapted content from Kwai, Kwai Insight, and Pear Video.

scholarly journals Classification of Tennis Video Types Based on Machine Learning Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xun Gong ◽  
Fucheng Wang
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Rapid Development ◽  
Video Data ◽  
Learning Technology ◽  
Video Content ◽  
Video Classification ◽  
The World ◽  
Spatial Detection

With the rapid development of online video data, how to find the required information has become an urgent problem to be solved. This article focuses on sports videos and studies video classification and content-based retrieval techniques. Its purpose is to establish a mark and index of video content and to promote user acquisition through computer processing, analysis, and understanding of video content. Video tennis classification has high research and application value. This article focuses on video tennis based on the selection of the basic frame of each shot and proposes an algorithm for classification of shots based on average grouping. Based on this, we use a color-coded spatial detection method to detect the type of tennis match. Then, it integrates the results of audiovisual analysis to identify and classify exciting events in tennis matches. According to statistics, although the number of people participating in tennis cannot enter the top ten, the number of spectators ranks fourth. Four tennis tournaments, masters, and crown tournaments are held every year around the world. Watching large-scale international tennis matches has become a pillar of leisure and vacation for many people. Tennis matches last from two hours to four hours or more, and there are countless large and small tennis matches around the world every year, so the number of tennis records created is staggering. And artificial intelligence technology is rarely used in tennis in the sports world (5%), but football has reached 50%. Therefore, when dealing with such a large amount of data, we urgently need to find a fast and effective video retrieval classification method to find the required information. The experiment of tennis video classification research based on machine learning technology proves that the accuracy of tennis video classification reaches 98%, so this system has high feasibility.

scholarly journals Development of Pathological Super-resolution Images using Artificial Intelligence based on Whole Slide Image

2020 ◽  
Author(s):  
Yang Deng ◽  
Min Feng ◽  
Yong Jiang ◽  
Yanyan Zhou ◽  
Hangyu Qing ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Large Scale ◽  
Rapid Development ◽  
Subjective Evaluation ◽  
Super Resolution ◽  
Computer Assisted ◽  
Uterine Leiomyosarcoma ◽  
Whole Slide Image ◽  
Resolution Process ◽  
Slide Image

Abstract Background: Pathology plays a very important role in the cancer diagnosis, as the gold standard for the identification of tumors. The rapid development of digital pathology (DP) which based on Whole Slide Image (WSI) has led to many improvements in telepathological consultation, digital management, and computer-assisted diagnosis by artificial intelligence (AI). In DP, the common digitization strategy is to scan the pathology slice with X20 or X40 objective. Usually, the X40's WSI is 4 times bigger than the X20's, and obviously, the storage space and transmission time of the data should be 4 times. These increased costs will be great negative factor in the popularization of DP. But at the same time, some cases have to use the high magnification WSI for reliable diagnosis. Methods: In this article, we present a novel super-resolution process which could be used for WSI through Deep Learning. This process powered by AI, have the ability to switch X20 WSI to X40 without loss of whole and locally features. Furthermore, we collect the examples of WSI data of patients with 100 uterine leiomyosarcoma and adult granulosa cell tumor (AGCT) of ovary respectively, which are used to test our super-resolution process. Results: We used the peak signal-to-noise ratio (PSNR), the structural similarity (SSIM), and the Blind/Referenceless Image Spatial QUality Evaluator (BRISQUE) to test the resulting X40 WSI synthesized by the super-resolution (SR), which were 42.03, 0.99 and 49.22 . Then, we tested our SR images from subjective evaluation of the pathologist's perspective, and tested that if the pathologists could objectively distinguish the images between SR and high-resolution (HR), to further confirm the consistency between our SR images and the real HR images. Conclusions: The testing results indicate that the X40 WSI synthesized by the super-resolution matches the performance of the one generated from the X40 objective in diagnosis of both tumors. We believe that this is a reliable method can be used in a variety of tumors' digital slides, and will be available for a large scale in clinical pathology as an innovative technique.

scholarly journals Personalized Marketing Recommendation System of New Media Short Video Based on Deep Neural Network Data Fusion

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Feifeng Huang
Keyword(s):  
Neural Network ◽  
Social Media ◽  
New Media ◽  
Recommendation System ◽  
Rapid Development ◽  
Mobile Internet ◽  
Data Set ◽  
Data Volume ◽  
Short Video ◽  
Specific Implementation

With the rapid development of mobile Internet, short video has become another darling after traditional webcast in recent years. How to make full use of short video for effective marketing has become a hot issue that academia and industry are paying close attention to. This article is mainly aimed at exploring practical new media through in-depth research and exploration of the specific implementation methods and strategies of short video marketing in social media, based on the advantages and characteristic models of short video marketing in social media. The strategy of short video marketing in social media, and the use of highly in-depth neural network analysis technology for the personalized marketing recommendation system of new media short videos, so as to better promote the use of social media short videos by enterprises or individuals. We have to learn from marketing activities. The experimental results of this article show that when the data volume reaches 80%, the performance of the VRBCH algorithm steadily improves, so the performance of the main F of the VRBCH algorithm is still relatively ideal when the data volume changes. Due to the high dilution of the experimental data set, the amount of data in the VRBCH algorithm has increased sharply by 30% to 35%, but the purchase rate of the marketing recommendation system is as high as 98%. Therefore, the system has high feasibility.

The Oxford Handbook of Ethics of AI

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Rapid Development ◽  
Data Driven ◽  
International Human Rights Law ◽  
Human Knowledge ◽  
Human Rights Law ◽  
Ai Ethics ◽  
And Behavior ◽  
Control Complex

This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

Research on the application strategy of new media technology in Modern University Law Teaching

2021 ◽  
pp. 1-6
Author(s):  
Shen Min
Keyword(s):  
College Students ◽  
New Media ◽  
Rapid Development ◽  
Media Technology ◽  
Teaching Mode ◽  
Innovative Teaching ◽  
Online Simulation ◽  
Mode Behavior ◽  
Deep Integration ◽  
Interactive Dynamic

The arrival of the new media era has a certain impact on the teaching environment of universities in China. The rapid development of new media has also profoundly affected the thinking mode, behavior style and psychological consciousness of college students. This paper puts forward some innovative teaching modes under the background of new media information technology, including the online simulation court, the construction of interactive dynamic teaching website and so on. It realizes the deep integration between law teaching and modern new media technology, and gradually forms an open and diversified teaching mode. The research content of this paper has far-reaching significance for promoting the teaching of new media technology and enhancing the pertinence and effectiveness of College Students’ legal education.

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