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関連する概念動画

Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
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Natural and Artificial Concepts01:24

Natural and Artificial Concepts

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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Components of Language01:24

Components of Language

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Language Development01:22

Language Development

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
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Language and Cognition01:27

Language and Cognition

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

376
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans
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タイムラル・ビジュアル・セマンティクス・インダクテッド・ヒューマン・モーション・インテリジェンスと大型言語モデル

Zheng Xing, Weibing Zhao

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |February 19, 2026
    PubMed
    まとめ
    この要約は機械生成です。

    この研究では,監視されていない人間の運動セグメンテーションを改善するために,大型言語モデル (LLM) を使用した人間の運動シーケンスからタイムビジョンセマンティクス (TVS) を導入します. この新しいアプローチは,より高い精度のために,LLMから派生したテキスト運動情報を統合することにより,サブスペースクラスタリングを強化します.

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    Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
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    科学分野:

    • コンピュータビジョン コンピュータビジョン
    • 機械学習 (Machine Learning) とは,機械学習 (Machine Learning) について学ぶことです.
    • 人工知能 (AI) とは,人工知能 (AI) のことです.

    背景:

    • 無監督ヒューマンモーションセグメンテーション (HMS) は,伝統的にサブスペースクラスタリングに依存しています.
    • 既存の方法は,モーションシーケンスにおける時間的な意味論理解の重要な側面をしばしば無視しています.
    • 視覚情報とテキスト情報の統合は,AI研究における成長傾向です.

    研究 の 目的:

    • 臨時視力セマンティクス (TVS) を組み込むことにより,無監督の人間の運動セグメンテーションを強化する.
    • 運動に関連するテキスト情報を抽出するために,大型言語モデル (LLM) の画像からテキストへの能力を活用する.
    • TVSを統合した新しいサブスペース・クラスタリング・フレームワークを開発し,セグメンテーションパフォーマンスを向上させる.

    主な方法:

    • フレーム対フレームのモーション類似性をクエリすることによって,LLMを使用して人間のモーションシーケンスからTVSの抽出.
    • タイムリーレギュラライザーでTVSに統合されたサブスペースクラスタリングのアプローチの開発.
    • セグメンテーション出力に基づくサブスペースエンブレディングの継続的な最適化のためのフィードバック対応のフレームワークの実装.

    主要な成果:

    • 提案された方法は,人間の動きに関する4つのベンチマークデータセットに関する既存の最先端のアプローチを大幅に上回る.
    • TVSの統合は,HMSのサブスペースクラスタリングのパフォーマンスを効果的に向上させます.
    • テンポラル・レギュラーライザーとコンストラクションは,類似のモーション・セマンティクスを持つフレームを成功裏にグループ化する.

    結論:

    • LLMを通じて派生したタイムビジョンセマンティックは,監視されていない人間の運動セグメンテーションのための強力な新しい次元を提供します.
    • 提案されているTVSに統合されたサブスペースクラスタリング方法は,HMS.のための堅牢で効果的なソリューションを提供します.
    • 将来の研究は,動き分析におけるより豊かな意味論的理解のために,より洗練されたLLMの相互作用を探索することができます.