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関連する概念動画

The Uncertainty Principle04:08

The Uncertainty Principle

32.0K
Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
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Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
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Self-Awareness and Its Effects01:21

Self-Awareness and Its Effects

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Self-awareness is a psychological state in which the individual becomes the focal point of their attention. This inward focus transforms the self into an object of contemplation and assessment, influencing how individuals perceive their actions and their alignment with personal and societal standards.Triggers and Contexts for Self-AwarenessSelf-awareness can be activated by external stimuli that make individuals visually or audibly aware of themselves, such as mirrors, cameras, or recordings.
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Altered States of Awareness01:06

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Altered states of consciousness represent significant deviations from one's normal mental state. These deviations can range from subtle changes in awareness to profound transformations in perception, thought processes, and sensory experiences. Altered states of consciousness can be triggered by various factors, including drug use, meditation, hypnosis, illness, or even intense fatigue.
The ingestion of substances like stimulants or hallucinogens leads to chemical alterations in the brain...
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Subconsciousness and No Awareness01:15

Subconsciousness and No Awareness

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The concept of subconscious awareness refers to the processing of information below the level of conscious thought, which significantly influences both behaviors and decisions. It is also known as waking subconscious awareness. This complex level of cognition operates without the direct awareness of the individual, facilitating rapid and simultaneous handling of multiple information streams.
An illustrative example of subconscious processing is its role in problem-solving. Often, individuals...
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Uncertainty: Overview00:59

Uncertainty: Overview

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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関連する実験動画

Updated: Feb 7, 2026

Operation of the Collaborative Composite Manufacturing CCM System
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カモフラージュ物体検出における不確実性を認識した人間と機械の協調

Ziyue Yang1,2, Kehan Wang1,2, Yuhang Ming1,2

  • 1School of Computer Science, Hangzhou Dianzi University, Hangzhou, 310018 Zhejiang China.

Cognitive neurodynamics
|February 6, 2026
PubMed
まとめ
この要約は機械生成です。

本研究では、コンピュータビジョンとブレイン・コンピュータ・インターフェース（BCI）を統合した、カモフラージュ物体検出（COD）のための新しい人間と機械の協調を導入し、隠された物体の識別の精度と効率を高めます。

キーワード:
ブレイン・コンピュータ・インターフェースカモフラージュ物体検出コンピュータビジョン人間と機械の協調不確実性推定

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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科学分野:

  • コンピュータビジョン
  • 人間とコンピュータの相互作用
  • 生体医工学

背景:

  • カモフラージュ物体検出（COD）は、隠された物体の識別を必要とするアプリケーションにおいて極めて重要です。
  • 既存の方法は、複雑なカモフラージュに苦労することが多く、信頼性と効率の向上が必要とされています。
  • 人間と機械の協調は、補完的な強みを活用するための有望な道を提供します。

研究 の 目的:

  • カモフラージュ物体検出（COD）のための新しい人間と機械の協調フレームワークを開発すること。
  • コンピュータビジョン（CV）モデルと非侵襲的ブレイン・コンピュータ・インターフェース（BCI）を統合することにより、CODパフォーマンスを向上させること。
  • 複雑な検出タスクにおいて、システムの信頼性を向上させ、人間の認知負荷を軽減すること。

主な方法:

  • CV予測における不確実性を推定するためのマルチビューバックボーンを提案しました。
  • トレーニング中に不確実性推定を利用して、効率を高めました。
  • テスト中に低信頼度の予測に対して、RSVPベースのBCIを使用した人間評価システムを実装しました。

主要な成果:

  • CAMOデータセットで最先端の結果を達成し、バランス精度（BA）を4.56％、F1スコアを3.66％向上させました。
  • 上位参加者のパフォーマンスが大幅に向上したことを実証しました（BAで最大7.6％、F1で6.66％）。
  • モデルの信頼度と検出精度との間に強い相関があることを確認しました。

結論:

  • 提案されたフレームワークは、人間と機械の協調を通じてカモフラージュ物体検出を効果的に強化します。
  • 不確実性を認識したCVとBCIの統合は、システムの信頼性と効率を向上させます。
  • このアプローチは、現実世界の高度なCODアプリケーションと人間とコンピュータの相互作用の基盤を提供します。