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Biao Hou

Also published under: B. Hou

Publications
208
Citations
3,779
Publications by Year
20062025
Co-Authors:
Show All Co-Authors (287)
Image of author Biao Hou

Biao Hou

Also published under: B. Hou

Affiliation

Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education
School of Artificial Intelligence
Xidian University, Xi’an, Shaanxi, China

Publication Topics

Biography

Biao Hou (Member, IEEE) received the B.S. and M.S. degrees in mathematics from Northwest University, Xi'an, China, in 1996 and 1999, respectively, and the Ph.D. degree in circuits and systems from Xidian University, Xi'an, China, in 2003.,Since 2003, he has been with the Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education, Xidian University, where he is currently a Professor. His research interests include compressive sensing and synthetic aperture radar image interpretation.(Based on document published on 22 February 2023).
Publications
208
Citations
3,779
Publications by Year
20062025
Co-Authors:
Show All Co-Authors (287)
Author's Published Works

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Contour-Aware Dynamic Low-High Frequency Integration for Pan-Sharpening

Xiaoyu Yi;Hao Zhu;Pute Guo;Biao Hou;Bo Ren;Xiaotong Li;Xiaoteng Wang;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2025 | Volume: 63 | Journal Article |
Pan-sharpening is the process of fusing panchromatic (PAN) and multispectral (MS) images. Its critical focus lies in accurately capturing the contour information from the PAN image during the fusion process and presenting it at a high resolution. However, existing deep learning methods lack the precise capture of delicate and smooth contour information, resulting in contour diffusion that affects ...Show More

Contour-Aware Dynamic Low-High Frequency Integration for Pan-Sharpening

Xiaoyu Yi;Hao Zhu;Pute Guo;Biao Hou;Bo Ren;Xiaotong Li;Xiaoteng Wang;Licheng Jiao

Year: 2025 | Volume: 63 | Journal Article |

Interactive Concept Network Enhanced Transformer for Remote Sensing Image Captioning

Cheng Zhang;Zhongle Ren;Biao Hou;Jianhua Meng;Weibin Li;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2025 | Volume: 63 | Journal Article |
Remote sensing image captioning plays an important role in advancing remote sensing image understanding with natural language generation. However, it is difficult to generate accurate semantic descriptions of crucial objects and their relationships, due to large coverage and abundant information in remote sensing images. To address these issues, this article proposes a novel interactive concept ne...Show More

Interactive Concept Network Enhanced Transformer for Remote Sensing Image Captioning

Cheng Zhang;Zhongle Ren;Biao Hou;Jianhua Meng;Weibin Li;Licheng Jiao

Year: 2025 | Volume: 63 | Journal Article |

Machine Learning-Based Modeling and BV Optimization for LDMOS With Multifloating Buried Layers

Zhen Cao;Qi Sun;Qiaowei Peng;Biao Hou;Licheng Jiao;Yintang Yang

IEEE Transactions on Electron Devices
Year: 2025 | Volume: 72, Issue: 2 | Journal Article |
This article introduces a novel approach that leverages machine learning (ML) to optimize the breakdown voltage (BV) of lateral double-diffused MOSFET (LDMOS) devices featuring multifloating buried layers (MFBLs). Moving away from the traditional, complex physical derivation methods, our research integrates neural networks with genetic algorithms to forge an adaptive optimization framework. Initia...Show More

Machine Learning-Based Modeling and BV Optimization for LDMOS With Multifloating Buried Layers

Zhen Cao;Qi Sun;Qiaowei Peng;Biao Hou;Licheng Jiao;Yintang Yang

Year: 2025 | Volume: 72, Issue: 2 | Journal Article |

Water-Matching CAM: A Novel Class Activation Map for Weakly-Supervised Semantic Segmentation of Water in SAR Images

Kai Wang;Zhongle Ren;Biao Hou;Feng Sha;Zhiyang Wang;Weibin Li;Licheng Jiao

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2025 | Volume: 18 | Journal Article |
Recently, semantic segmentation of water in synthetic aperture radar (SAR) images has attracted the attention of more and more scholars. However, existing methods usually require many accurate manually labeled pixel-level water annotations of SAR images, which leads to the problem that they are often time-consuming and costly. To mitigate this problem, we apply the weakly-supervised semantic segme...Show More

Water-Matching CAM: A Novel Class Activation Map for Weakly-Supervised Semantic Segmentation of Water in SAR Images

Kai Wang;Zhongle Ren;Biao Hou;Feng Sha;Zhiyang Wang;Weibin Li;Licheng Jiao

Year: 2025 | Volume: 18 | Journal Article |

Industrial-Mass Mini/Micro LED Sorting Using Patch Enhanced Lightweight Self-Attention Hybrid Neural Network

Jie Chu;Jueping Cai;Biao Hou;Kailin Wen

IEEE Transactions on Industrial Informatics
Year: 2025 | Volume: 21, Issue: 1 | Journal Article |
Mini/Micro LEDs are becoming the next generation of displays, with sizes shrinking to less than 100 μm/50 μm and integration scaling increasing by more than 100-fold. Fast and precise sorting, which includes the identification and localization of mass mini/micro LED chips, has become an urgent need in the industry due to its high efficiency and reliability. However, the small size, high density, a...Show More

Industrial-Mass Mini/Micro LED Sorting Using Patch Enhanced Lightweight Self-Attention Hybrid Neural Network

Jie Chu;Jueping Cai;Biao Hou;Kailin Wen

Year: 2025 | Volume: 21, Issue: 1 | Journal Article |

Cost-Effective and High-Speed Implementation of Brain-Like Spiking Neural Network with Encoding Architectures on FPGA

Zhen Cao;Ziyi Zhang;Qi Sun;Biao Hou;Licheng Jiao;Yintang Yang

CHAIN
Year: 2024 | Volume: 1, Issue: 2 | Journal Article |
The spiking neural network (SNN) is the third generation of neural networks, valued for its biological interpretability, hardware compatibility, and low power consumption. While field programmable gate array (FPGA), based SNN accelerators show promise with their intelligent design and low power consumption, existing models lack a crucial spiking encoding module. This leads to increased pre-process...Show More

Cost-Effective and High-Speed Implementation of Brain-Like Spiking Neural Network with Encoding Architectures on FPGA

Zhen Cao;Ziyi Zhang;Qi Sun;Biao Hou;Licheng Jiao;Yintang Yang

Year: 2024 | Volume: 1, Issue: 2 | Journal Article |

Joint Style and Layout Synthesizing: Toward Generalizable Remote Sensing Semantic Segmentation

Qi Zang;Shuang Wang;Dong Zhao;Zhun Zhong;Biao Hou;Licheng Jiao

IEEE Transactions on Circuits and Systems for Video Technology
Year: 2024 | Early Access Article |
This paper studies the domain generalized remote sensing semantic segmentation (RSSS), aiming to generalize a model trained only on the source domain to unseen domains. Existing methods in computer vision treat style information as domain characteristics to achieve domain-agnostic learning. Nevertheless, their generalizability to RSSS remains constrained, due to the incomplete consideration of dom...Show More

Joint Style and Layout Synthesizing: Toward Generalizable Remote Sensing Semantic Segmentation

Qi Zang;Shuang Wang;Dong Zhao;Zhun Zhong;Biao Hou;Licheng Jiao

Year: 2024 | Early Access Article |

Rebalancing Gaussian Location Loss for High-Precision Detection on Remote Sensing Images

Zhonghua Li;Biao Hou;Zitong Wu;Xianpeng Guo;Bo Ren;Zhongle Ren;Chen Yang;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Aerial image objects are usually orientated arbitrarily, with a large scale range, and densely distributed. Traditional horizontal bounding box (HBB) detectors tend to filter out densely distributed objects leading to missed detections, such as ship (SH) and vehicle. Therefore, oriented object detection has become a mainstream solution in recent years. The 2-D Gaussian distribution representation ...Show More

Rebalancing Gaussian Location Loss for High-Precision Detection on Remote Sensing Images

Zhonghua Li;Biao Hou;Zitong Wu;Xianpeng Guo;Bo Ren;Zhongle Ren;Chen Yang;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

MSRIP-Net: Addressing Interpretability and Accuracy Challenges in Aircraft Fine-Grained Recognition of Remote Sensing Images

Zhengxi Guo;Biao Hou;Xianpeng Guo;Zitong Wu;Chen Yang;Bo Ren;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
The task of fine-grained aircraft recognition is crucial in the field of remote sensing. Despite some progress achieved by traditional deep learning methods in addressing this challenge, they are often perceived as a “black box,” lacking transparent explanations for model decisions. Current interpretable methods based on attention mechanisms, although providing some interpretability, do not align ...Show More

MSRIP-Net: Addressing Interpretability and Accuracy Challenges in Aircraft Fine-Grained Recognition of Remote Sensing Images

Zhengxi Guo;Biao Hou;Xianpeng Guo;Zitong Wu;Chen Yang;Bo Ren;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

MSGFusion: Muti-scale Semantic Guided LiDAR-Camera Fusion for 3D Object Detection

Huming Zhu;Yiyu Xue;Xinyue Cheng;Biao Hou

2024 International Joint Conference on Neural Networks (IJCNN)
Year: 2024 | Conference Paper |
3D object detection is a key technology in automatic driving perception, which can provide the basis for safe and reliable autonomous driving. Aiming at the problem of false positive of low resolution object in point clouds, we present Multi-scale Semantic Guided LiDAR-Camera Fusion for 3D Object Detection(MSGFusion), which deeply fuses the features of image and LiDAR points. Specifically, we desi...Show More

MSGFusion: Muti-scale Semantic Guided LiDAR-Camera Fusion for 3D Object Detection

Huming Zhu;Yiyu Xue;Xinyue Cheng;Biao Hou

Year: 2024 | Conference Paper |

Adaptive Feature Separation Network for Remote Sensing Object Detection

Wenping Ma;Yiting Wu;Hao Zhu;Wenhao Zhao;Yue Wu;Biao Hou;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
With the development of remote sensing technology, remote sensing object detection has been widely applied in various fields, but it still faces some thorny challenges, such as the following: 1) the complexity of object scale changes in remote sensing images makes it difficult to improve the performance of small object detection and 2) remote sensing images have complex backgrounds and densely arr...Show More

Adaptive Feature Separation Network for Remote Sensing Object Detection

Wenping Ma;Yiting Wu;Hao Zhu;Wenhao Zhao;Yue Wu;Biao Hou;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

MGPACNet: A Multiscale Geometric Prior Aware Cross-Modal Network for Images Fusion Classification

Xue Song;Licheng Jiao;Lingling Li;Fang Liu;Xu Liu;Shuyuan Yang;Biao Hou

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Convolutional neural networks (CNNs) and self-attention (SA) are highly effective techniques used for the fusion of multisource remote sensing (RS) data, and they have found extensive application in Earth observation (EO) tasks. Nevertheless, CNNs are insufficient for the comprehensive extraction of contextual information and the representation of the sequential properties of spectral features. Fu...Show More

MGPACNet: A Multiscale Geometric Prior Aware Cross-Modal Network for Images Fusion Classification

Xue Song;Licheng Jiao;Lingling Li;Fang Liu;Xu Liu;Shuyuan Yang;Biao Hou

Year: 2024 | Volume: 62 | Journal Article |

Subpixel Feature Pyramid Network for Multiscale Ship Detection in Synthetic Aperture Radar Remote Sensing Images

Ming Liu;Biao Hou;Bo Ren;Licheng Jiao;Zhi Yang;Zongwei Zhu

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2024 | Volume: 17 | Journal Article |
Synthetic aperture radar (SAR) has been widely used in maritime domain awareness, especially in ship detection, due to the capability of working all-day and all-weather. In the detection of SAR ships, there are significant challenges in sea clutter, complex scenes, and especially for multiscale ships with varying sizes. In contrast to large-scale ships, small-scale ships in SAR images only occupy ...Show More

Subpixel Feature Pyramid Network for Multiscale Ship Detection in Synthetic Aperture Radar Remote Sensing Images

Ming Liu;Biao Hou;Bo Ren;Licheng Jiao;Zhi Yang;Zongwei Zhu

Year: 2024 | Volume: 17 | Journal Article |

A Semantically Nonredundant Continuous-Scale Feature Network for Panchromatic and Multispectral Classification

Hao Zhu;Wenhao Zhao;Xiaotong Li;Biao Hou;Changzhe Jiao;Zhongle Ren;Wenping Ma;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Cited by: Papers (1)
In recent years, panchromatic (PAN) images and multispectral (MS) images, as a type of multimodal remote sensing data, are attracting increasingly more attention to their classification problems. However, effectively representing size variations of targets in remote sensing images and reducing redundant representations of different modalities’ deep semantic features to enhance classification accur...Show More

A Semantically Nonredundant Continuous-Scale Feature Network for Panchromatic and Multispectral Classification

Hao Zhu;Wenhao Zhao;Xiaotong Li;Biao Hou;Changzhe Jiao;Zhongle Ren;Wenping Ma;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

ISSP-Net: An Interactive Spatial-Spectral Perception Network for Multimodal Classification

Wenping Ma;Hekai Zhang;Mengru Ma;Chuang Chen;Biao Hou

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Cited by: Papers (2)
Coordinated and complementary spatial-spectral information is represented by the panchromatic (PAN) and multispectral (MS) images. The optimal utilization of the advantages of these images has become a subject of intense research interest. This article introduces the interactive spatial-spectral perception network (ISSP-Net) for multimodal remote sensing image classification, addressing the challe...Show More

ISSP-Net: An Interactive Spatial-Spectral Perception Network for Multimodal Classification

Wenping Ma;Hekai Zhang;Mengru Ma;Chuang Chen;Biao Hou

Year: 2024 | Volume: 62 | Journal Article |

Renormalized Connection for Scale-Preferred Object Detection in Satellite Imagery

Fan Zhang;Lingling Li;Licheng Jiao;Xu Liu;Fang Liu;Shuyuan Yang;Biao Hou

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Satellite imagery, due to its long-range imaging, brings with it a variety of scale-preferred tasks, such as the detection of tiny/small objects, making the precise localization and detection of small objects of interest a challenging task. In this article, we design a knowledge discovery network (KDN) to implement the renormalization group theory in terms of efficient feature extraction (FE). Ren...Show More

Renormalized Connection for Scale-Preferred Object Detection in Satellite Imagery

Fan Zhang;Lingling Li;Licheng Jiao;Xu Liu;Fang Liu;Shuyuan Yang;Biao Hou

Year: 2024 | Volume: 62 | Journal Article |

A Review of DNN and GPU in Optical Proximity Correction

Huming Zhu;Xiangyu Jiang;Delong Shu;Xinyue Cheng;Biao Hou;Hailong You

2024 2nd International Symposium of Electronics Design Automation (ISEDA)
Year: 2024 | Conference Paper |
Optical Proximity Correction (OPC) is a resolution enhancement technique. It compensates for imaging distortions by modifying the mask patterns. In advanced nodes, inverse lithography technology (ILT) is used to produce more complex and finer mask shapes. However, ILT increases the computational complexity and runtime. In recent years, researchers have attempted to accelerate the process using GPU...Show More

A Review of DNN and GPU in Optical Proximity Correction

Huming Zhu;Xiangyu Jiang;Delong Shu;Xinyue Cheng;Biao Hou;Hailong You

Year: 2024 | Conference Paper |

Multi-View Feature Fusion and Visual Prompt for Remote Sensing Image Captioning

Shuang Wang;Qiaoling Lin;Xiutiao Ye;Yu Liao;Dou Quan;Zhongqian Jin;Biao Hou;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Remote sensing image (RSI) captioning is a vision-language multimodal task concentrating on both image comprehension and sentence generation. Several studies suggest that encoder–decoder-based methods have achieved success in RSI captioning. However, existing encoder–decoder-based methods may not fully explore image representations for RSI captioning and suffer from a lack of additional prompt inf...Show More

Multi-View Feature Fusion and Visual Prompt for Remote Sensing Image Captioning

Shuang Wang;Qiaoling Lin;Xiutiao Ye;Yu Liao;Dou Quan;Zhongqian Jin;Biao Hou;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

High-Low-Frequency Progressive-Guided Diffusion Model for PAN and MS Classification

Hao Zhu;Fengtao Yan;Pute Guo;Xiaotong Li;Biao Hou;Kefan Chen;Shuang Wang;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
With the rapid development of remote sensing technology, satellites can easily acquire multispectral (MS) and panchromatic (PAN) images. It is challenging to utilize their complementarity to effectively combine each other’s advantages and mitigate the differences between different modes. In this article, we propose a high-low-frequency progressive-guided diffusion model. It is used to generate an ...Show More

High-Low-Frequency Progressive-Guided Diffusion Model for PAN and MS Classification

Hao Zhu;Fengtao Yan;Pute Guo;Xiaotong Li;Biao Hou;Kefan Chen;Shuang Wang;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

ConvGRU-Based Multiscale Frequency Fusion Network for PAN-MS Joint Classification

Hao Zhu;Xiaoyu Yi;Xiaotong Li;Biao Hou;Changzhe Jiao;Wenping Ma;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Cited by: Papers (2)
As a hot research topic in remote sensing, effectively integrating the advantageous features of multispectral and panchromatic images is the main challenge for fusing these two remote sensing images. This article proposes a multiscale frequency fusion network based on ConvGRU. To address the underutilization of texture features, we extract multiscale bandpass and low-pass sub-bands representing te...Show More

ConvGRU-Based Multiscale Frequency Fusion Network for PAN-MS Joint Classification

Hao Zhu;Xiaoyu Yi;Xiaotong Li;Biao Hou;Changzhe Jiao;Wenping Ma;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

Few-Shot MS and PAN Joint Classification With Improved Cross-Source Contrastive Learning

Hao Zhu;Pute Guo;Biao Hou;Xiaotong Li;Changzhe Jiao;Bo Ren;Licheng Jiao;Shuang Wang

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
The joint classification of multispectral (MS) and panchromatic (PAN) images aims to provide a more detailed and accurate interpretation of land features. Although deep-learning-based methods have achieved remarkable success in this task, the generalization performance of networks is compromised when labeled samples are insufficient. In this study, we explore the possibility of leveraging unlabele...Show More

Few-Shot MS and PAN Joint Classification With Improved Cross-Source Contrastive Learning

Hao Zhu;Pute Guo;Biao Hou;Xiaotong Li;Changzhe Jiao;Bo Ren;Licheng Jiao;Shuang Wang

Year: 2024 | Volume: 62 | Journal Article |

SigDA: A Superimposed Domain Adaptation Framework for Automatic Modulation Classification

Shuang Wang;Hantong Xing;Chenxu Wang;Huaji Zhou;Biao Hou;Licheng Jiao

IEEE Transactions on Wireless Communications
Year: 2024 | Volume: 23, Issue: 10 | Journal Article |
Cited by: Papers (3)
Due to the uncertainty of non-cooperative communication channels, the received signals often contain various impairment factors, leading to a significant decline in the performance of existing deep learning (DL)-based automatic modulation classification (AMC) models. Several preliminary works utilize domain adaptation (DA) to alleviate this issue, however, they are constrained by singular domain d...Show More

SigDA: A Superimposed Domain Adaptation Framework for Automatic Modulation Classification

Shuang Wang;Hantong Xing;Chenxu Wang;Huaji Zhou;Biao Hou;Licheng Jiao

Year: 2024 | Volume: 23, Issue: 10 | Journal Article |

MGC: MLP-Guided CNN Pretraining Using a Small-Scale Dataset for Remote Sensing Images

Zhihao Li;Biao Hou;Wanqing Li;Zitong Wu;Bo Ren;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
To overcome the inherent domain gap between natural images and remote sensing images (RSIs), it is highly desirable to develop pretraining methods specifically for RSIs. Considering the lack of widely recognized large-scale benchmarks like ImageNet in the RSI community and limited computational resources, this article proposes multilayer perceptron (MLP)-guided convolutional neural network (CNN) (...Show More

MGC: MLP-Guided CNN Pretraining Using a Small-Scale Dataset for Remote Sensing Images

Zhihao Li;Biao Hou;Wanqing Li;Zitong Wu;Bo Ren;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review

Licheng Jiao;Mengru Ma;Pei He;Xueli Geng;Xu Liu;Fang Liu;Wenping Ma;Shuyuan Yang;Biao Hou;Xu Tang

IEEE Transactions on Neural Networks and Learning Systems
Year: 2024 | Early Access Article |
Cited by: Papers (3)
The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectively improve the intelligence of existing models and systems. Compared with other reviews, this article provides a comprehensive review of brain-inspir...Show More

Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review

Licheng Jiao;Mengru Ma;Pei He;Xueli Geng;Xu Liu;Fang Liu;Wenping Ma;Shuyuan Yang;Biao Hou;Xu Tang

Year: 2024 | Early Access Article |

Self-Supervised Learning Guided by SAR Image Factors for Terrain Classification

Zhongle Ren;Zhe Du;Shaobo Liu;Biao Hou;Weibin Li;Hao Zhu;Bo Ren;Licheng Jiao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Cited by: Papers (1)
Effective feature representation is the key to synthetic aperture radar (SAR) image terrain classification. Limited by the abstract appearance and the scarcity of high-quality labeled data in this field, the features learned by current methods, especially deep learning models, do not have enough directivity and applicability, which hampers the performance. This article proposes multi-image factor ...Show More

Self-Supervised Learning Guided by SAR Image Factors for Terrain Classification

Zhongle Ren;Zhe Du;Shaobo Liu;Biao Hou;Weibin Li;Hao Zhu;Bo Ren;Licheng Jiao

Year: 2024 | Volume: 62 | Journal Article |

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