2024年4月23日 · Abstract: To meet the urgent demand for high efficiency and high power density inductive power transfer (IPT) system in key applications such as electric vehicles, deep-sea intelligent equipment and consumer electronics, this article proposes a novel IPT system with full range soft-switching operation and magnetic integrated structure based on ...

Inductive power transfer (IPT) was an engineering curiosity less than 30 years ago, but, at that time, it has grown to be an important technology in a variety of applications. The paper looks at the background to IPT and how its development was based on sound engineering principles leading on to factory automation and growing to a $1 billion ...

2021年8月29日 · IPT模型采用多头多尾共享的变压器体，用于图像超分辨率和去噪等不同的图像处理任务。 为了最大限度地挖掘Transformer结构在各种任务上的性能，探索了一个合成的ImageNet数据集。 对比学习的加入稳定、提升Transformer

2022年11月30日 · Tausch starts the show with a quick recap of his night at the Wisconsin basketball game, followed by a question from his time off last week asking if it's "In Poor Taste" or not to use the handicap-accessible stall in a bathroom? Also, Aaron Rodgers is all about "competitive greatness" when saying he wants to play against the Bears this weekend.

This article constructs a family of hybrid IPT topologies, including input-parallel-output-parallel, input-parallel-output-series, input-series-output-parallel (ISOP), and input-series-output-series for delivering a constant current (CC) or a constant voltage (CV).

2022年12月1日 · Tausch is a novel header-only library that provides a simple API for efficiently handling these types of data movements. Tausch supports both simple CPU-only systems, but also more complex heterogeneous systems with both CPUs and GPUs.

2025年1月31日 · IPT (Image Processing Transformer) 便是其中的代表作之一，通过大规模预训练和多任务学习，展现了在 SR、去噪、去雨等图像处理任务上的优秀性能。 将输入图像分割成若干 Patch，展平后加上位置编码，再送入 Transformer 编码器，实现并行全局建模。 Transformer 传统上在 NLP 场景对序列 tokens 应用多头自注意力。 对于图像，可以视**图像块（Patch）**为 tokens，并在高维空间映射后输入 Transformer： 3 p 2 3p^2 3p2。

这篇论文利用ImageNet训练了一个能降噪、超分和去雨的图像预训练模型（IPT）。 论文链接： arxiv.org/abs/2012.0036. 目前很多low-level的task其实都是有一定相关性的，就是在一个low-level task上预训练对另一个task是有帮助的，但是目前几乎没有人去做相关的工作。 而且 pre-training 在某些数据稀缺的task上就很有必要，并且无论在CV还是NLP，使用pre-trained model是非常常见的事情。 对于一些输入和输出都是image的low-level算法来说，目前的pre-trained model显然 …

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2020年7月17日 · This study proposes a misalignment-tolerant integrated inductive power transfer (IPT) system for tram logistics robots and presents an adapted parameter tuning method for the IPT system.