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関連する概念動画

Velocity of an Object01:18

Velocity of an Object

213
Understanding how an object moves along a path requires distinguishing between motion over a time span and motion at a precise moment. A useful example is a vehicle traveling along a straight and level path, where its position at any given time is known. The initial step in analyzing this motion is to measure how far the vehicle travels over a fixed time period. This measurement, called average velocity, is computed by dividing the total change in position by the duration over which the change...
213
Potential Due to a Polarized Object01:29

Potential Due to a Polarized Object

813
A neutral atom consists of a positively charged nucleus surrounded by a negatively charged electron cloud. When placed in an external electric field, the external electric force pulls the electrons and nucleus apart, opposite to the intrinsic attraction between the nucleus and the electrons. The opposing forces balance each other with a slight shift between the center of masses of the nucleus and the electron cloud, resulting in a polarized atom. On the other hand, a few molecules, like water,...
813
Potential Due to a Magnetized Object01:24

Potential Due to a Magnetized Object

829
Magnetic dipoles in magnetic materials are aligned when placed under an external magnetic field. For paramagnets and ferromagnets, dipole alignment occurs in the direction of the magnetic field. However, the dipoles align opposite to the field in the case of diamagnets. This state of magnetic polarization due to the external field is called magnetization. Magnetization is defined as the dipole moment per unit volume. It plays a similar role to polarization in electrostatics.
The vector...
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Attention-Deficit/Hyperactivity Disorder01:30

Attention-Deficit/Hyperactivity Disorder

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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and impulsivity. It affects approximately 5-8% of children globally, with around 60-70% of cases persisting into adulthood. ADHD has significant implications for educational attainment, social interactions, and occupational success.
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings....
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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
430
Moment of Inertia of Compound Objects01:07

Moment of Inertia of Compound Objects

7.7K
The moment of inertia is a quantitative measure of the rotational inertia of an object. It is defined as the sum of the products obtained by multiplying the mass of each particle of matter in a given body by the square of its distance from the axis. The total moment of inertia for compound objects can be found by determining and adding the moment of inertia of individual components together.
Consider a child of mass (mc) 25 kg standing at a distance (rc) of 1 m from the axis of a rotating...
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Updated: Feb 15, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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ASDTracker: 効率的なマルチオブジェクトトラッキングのための注意を誘導した精細化と適応的に希少な検出.

Yueying Wang, Chenyang Yan, Cairong Zhao

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |February 13, 2026
    PubMed
    まとめ
    この要約は機械生成です。

    本研究では,効率的なマルチオブジェクトトラッキング (MOT) 方法であるASDTrackerを紹介しています. 精度とスピードのバランスを取るために検出器を適応的に使用し,自動運転車などのアプリケーションのリアルタイムパフォーマンスを実現します.

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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
    • 人工知能 (AI) とは,人工知能 (AI) のことです.
    • ロボット工学 ロボット工学 ロボット工学

    背景:

    • トラッキング・バイ・デテクション (Tracking-by-Detection) 方法は,マルチオブジェクト・トラッキング (MOT) に有効ですが,計算上は高価です.
    • 高い計算負荷は,検出および再識別 (ReID) プロセスから生じる.
    • リアルタイムアプリケーションには,効率的なMOTソリューションが必要です.

    研究 の 目的:

    • 高性能を維持する効率的な追跡による検出アルゴリズム (ASDTracker) を開発する.
    • 検出器の使用を適応的に管理することにより,コンピューティングの負担を軽減します.
    • リアルタイムMOTを,無人地表車両などのアプリケーションに有効にするために.

    主な方法:

    • ASDTrackerは,注意を誘導した精細化による適応的に稀な検出を採用しています.
    • 閉塞を動的に評価して,高価な検出器の使用時期を決定します.
    • Refinementネットワークは,非キーフレームの騒々しい影ラベルで訓練され,重いReIDネットワークの代わりに軽量な外観機能を使用しています.

    主要な成果:

    • ASDTrackerは,4つのベンチマークで競争力のある一般化と堅実性を達成しています.
    • 既存の方法と比較して有利な推論速度を示しています.
    • 高い精度と低遅延で無人地表車両に成功した.

    結論:

    • ASDTrackerは,リアルタイムで複数のオブジェクトを追跡するための効率的かつ効果的なソリューションを提供します.
    • 適応的アプローチは,計算コストと追跡精度をうまくバランスとします.
    • この方法は,低遅延の知覚を必要とする現実世界のロボットアプリケーションに希望を示しています.