Han Zhou


Last Name

Zhou

First Name

Han

ORCID

0000-0003-0014-5317

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2023 - 20253
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Publications 1 - 3 of 3
  • A 25-40 GHz Three-Way Power Amplifier with No Load ModulationAchieving Broadband Deep Power Back-Off Efficiency Enhancement
    Item type: Conference Paper
    Liu, Edward; Zhou, Han; Fager, Christian; et al. (2024)
    2024 IEEE Radio Frequency Integrated Circuits Symposium (RFIC)
    This paper presents a millimeter-wave (mm-Wave) power amplifier (PA) topology that avoids the trade-off between bandwidth and load modulation. The proposed topology uses three PA paths and can achieve efficiency enhancement at power back-off without load modulation. With a 100 MHz 5G NR FR2 1-CC 64-QAM signal, this PA achieves P-AVG and PAE(AVG) of 6.45 - 12.61 dBm and 5.9 - 16.4% from 25 - 40 GHz, respectively. With a 200 MHz, signal, P-AVG and PAE(AVG) are 5.58 - 11.1 dBm and 4.8 - 13.3%, respectively.
  • Instructive Feature Enhancement for Dichotomous Medical Image Segmentation
    Item type: Conference Paper
    Liu, Lian; Zhou, Han; Chen, Jiongquan; et al. (2023)
    Lecture Notes in Computer Science ~ Medical Image Computing and Computer Assisted Intervention – MICCAI 2023
    Deep neural networks have been widely applied in dichotomous medical image segmentation (DMIS) of many anatomical structures in several modalities, achieving promising performance. However, existing networks tend to struggle with task-specific, heavy and complex designs to improve accuracy. They made little instructions to which feature channels would be more beneficial for segmentation, and that may be why the performance and universality of these segmentation models are hindered. In this study, we propose an instructive feature enhancement approach, namely IFE, to adaptively select feature channels with rich texture cues and strong discriminability to enhance raw features based on local curvature or global information entropy criteria. Being plug-and-play and applicable for diverse DMIS tasks, IFE encourages the model to focus on texture-rich features which are especially important for the ambiguous and challenging boundary identification, simultaneously achieving simplicity, universality, and certain interpretability. To evaluate the proposed IFE, we constructed the first large-scale DMIS dataset Cosmos55k, which contains 55,023 images from 7 modalities and 26 anatomical structures. Extensive experiments show that IFE can improve the performance of classic segmentation networks across different anatomies and modalities with only slight modifications. Code is available at https://github.com/yezi-66/IFE.
  • A Ka-Band Doherty-Like Non-Load Modulated Power Amplifier
    Item type: Journal Article
    Liu, Edward; Zhou, Han; Fager, Christian; et al. (2025)
    IEEE Journal of Solid-State Circuits
    This article describes a three-way power amplifier (PA) topology that achieves broadband power back-off (PBO) efficiency enhancement without using active load modulation on the Main PA or supply modulation. This allows the PA to avoid the classic trade-off between load modulation and bandwidth that is typical among Doherty PAs. Unlike Doherty PAs, the proposed PA has both its voltage and current drive profiles reach a maximum at PBO, which causes the impedance of the Main PA to be constant across the entire input drive. This is achieved with a novel parallel-series output matching network (OMN) that primarily utilizes coupled-line baluns. A prototype is fabricated in the GlobalFoundries 45 nm RFSOI and achieves a P$_{avg}$ and PAE$_{avg}$ of 6.45-12.61 dBm and 5.9%-16.4% from 25 to 40 GHz, respectively. With a 200 MHz signal, P$_{avg}$ and PAE$_{avg}$ are 5.58-11.1 dBm and 4.8%-13.3%, respectively.
Publications 1 - 3 of 3