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相关概念视频

Stereotype Content Model02:16

Stereotype Content Model

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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Behavior Modification01:21

Behavior Modification

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Behavioral approaches have often been criticized for ignoring mental processes and focusing solely on observable behavior. However, these approaches provide an optimistic perspective for individuals seeking to change their behaviors. Rather than concentrating on intrinsic personality traits, behavioral approaches suggest that even longstanding habits can be modified by changing the reward contingencies that maintain them.
A real-world application of operant conditioning principles is applied...
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Case Studies01:22

Case Studies

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There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it.
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Behaviorism01:28

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The field of behaviorism was pioneered by figures such as Ivan Pavlov, John B. Watson, and B.F. Skinner fundamentally shifted the focus of psychology to the observable and controllable aspects of human and animal behavior. This shift marked a critical evolution in the discipline, emphasizing scientific rigor and experimental methodology.
The core premise of behaviorism is its focus on observable behavior rather than internal thoughts or feelings. This approach argues that true scientific...
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Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

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Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
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Modeling in Therapy01:26

Modeling in Therapy

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Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
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Automated Interactive Video Playback for Studies of Animal Communication
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适应性视频总结的行为分析:从概括到个性化

Payal Kadam1,2, Deepali Vora1, Shruti Patil1

  • 1Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University) (SIU), Lavale, Pune, Maharashtra, India.

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概括
此摘要是机器生成的。

本研究介绍了一种两阶段方法,使用机器学习和用户参与来总结视频. 它通过通过个性化内容策划来提高可访问性和导航性来解决管理CCTV录像的挑战.

关键词:
深度学习,计算机视觉深度排序算法 深度排序算法信息检索 信息检索关键框提取 基于单视图查询 视频总结 视频总结基于查询的总结基于查询的总结视频总结 视频总结在YOLO V5中,你会看到YOLO V5.

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相关实验视频

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Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
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科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 多媒体系统 多媒体系统

背景情况:

  • 管理大量的多媒体内容,特别是CCTV录像,在存储,可访问性和有效导航方面提出了重大挑战.
  • 现有的视频总结技术往往缺乏个性化,并与数字视频数据的庞大规模作斗争.

研究的目的:

  • 开发一种综合的视频总结技术,将机器学习与用户参与融合在一起.
  • 解决存储,可访问性和导航在管理多媒体内容,特别是CCTV录像中的挑战.
  • 为了增强用户交互并个性化视频摘要的内容策划.

主要方法:

  • 第一个阶段:基于关键检测和行为分析的视频总结,使用YOLOv5进行对象识别,使用Deep SORT进行对象跟踪和使用单击检测器 (SSD).
  • 第二阶段:基于用户兴趣的视频总结,由机器学习驱动,结合用户偏好进行个性化内容策划.
  • 利用自然语言工具包 (NLTK),OpenCV,TensorFlow和EfficientDET模型进行定制的视频摘要生成.

主要成果:

  • 通过客观分析和以用户为中心的个性化改进视频总结的双阶段方法.
  • 增强在数字平台上处理大量视频数据的能力.
  • 根据个人用户偏好的定制视频摘要的生成.

结论:

  • 提出的创新方法有效地解决了管理多媒体数据的复杂挑战.
  • 将机器学习技术与用户参与相结合,在视频总结方面取得了重大进展.
  • 该系统增强了用户交互,并为数字内容管理提供了高效的解决方案.