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Related Concept Videos

Three-Winding Transformers01:19

Three-Winding Transformers

216
Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
216
The Ideal Transformer01:26

The Ideal Transformer

369
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
369
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

404
The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
404
Types Of Transformers01:16

Types Of Transformers

954
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
954
Energy Losses in Transformers01:21

Energy Losses in Transformers

844
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
844
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

144
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
144

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Updated: Jun 15, 2025

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Correlation-Embedded Transformer Tracking: A Single-Branch Framework.

Fei Xie, Wankou Yang, Chunyu Wang

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |August 22, 2024
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    Summary
    This summary is machine-generated.

    This study introduces a novel single-branch transformer-based tracker (SBT) for visual object tracking, improving robustness and discrimination. The enhanced SuperSBT model significantly boosts performance and speed on benchmark datasets.

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    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Traditional Siamese-based trackers struggle with robust and discriminative appearance modeling due to insufficient feature extraction.
    • Existing methods often focus on correlation operations, limiting simultaneous robustness and discrimination.

    Purpose of the Study:

    • To propose a novel single-branch tracking framework inspired by transformers for improved visual object tracking.
    • To develop a more efficient and effective tracker by enhancing the single-branch approach.

    Main Methods:

    • A single-branch tracking framework (SBT) using transformers with deep, multi-layer cross-image feature correlation was developed.
    • The SuperSBT model incorporates a hierarchical architecture, local modeling, unified relation modeling, and masked image modeling pre-training.

    Main Results:

    • SuperSBT outperforms the SBT baseline by 4.7%, 3.0%, and 4.5% AUC on LaSOT, TrackingNet, and GOT-10K, respectively.
    • SuperSBT significantly increases tracking speed from 37 FPS to 81 FPS compared to SBT.
    • The proposed method achieves superior results across eight visual object tracking benchmarks.

    Conclusions:

    • The transformer-based single-branch approach effectively addresses limitations in Siamese-based trackers.
    • SuperSBT offers a state-of-the-art solution for visual object tracking, balancing high accuracy and speed.