Hongwei Zhao
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View article: Downscaling Method for Crop Yield Statistical Data Based on the Standardized Deviation from the Mean of the Comprehensive Crop Condition Index
Downscaling Method for Crop Yield Statistical Data Based on the Standardized Deviation from the Mean of the Comprehensive Crop Condition Index Open
Spatializing crop yield statistical data with administrative divisions as the basic unit helps reveal the spatial distribution characteristics of crop yield and provides necessary spatial information to support field management and governm…
View article: A Real Time Bird Nest Detector for Railway Catenary Safety Inspection
A Real Time Bird Nest Detector for Railway Catenary Safety Inspection Open
With the rapid development of China’s high-speed railway network, contact network online inspection based on on- board video has become an essential method for ensuring the safety of the power supply system. However, existing detection mod…
View article: Photosynthetic performance and sucrose metabolism in superior and inferior rice grains with overlapping growth stages under water stress
Photosynthetic performance and sucrose metabolism in superior and inferior rice grains with overlapping growth stages under water stress Open
View article: A 10-meter resolution dataset of abandoned and reclaimed cropland from 2016 to 2023 in Inner Mongolia, China
A 10-meter resolution dataset of abandoned and reclaimed cropland from 2016 to 2023 in Inner Mongolia, China Open
Amid growing global food security concerns and frequent armed conflicts, real-time monitoring of abandoned cropland is essential for strategic planning and crisis management. This study develops a method to map abandoned cropland accuratel…
View article: Temporal segmentation method for 30-meter long-term mapping of abandoned and reclaimed croplands in Inner Mongolia, China
Temporal segmentation method for 30-meter long-term mapping of abandoned and reclaimed croplands in Inner Mongolia, China Open
At the end of the last century, the expansion of agricultural land in the arid and semi-arid regions of northern China intensified the conflict between agricultural development and ecological protection. Accurately mapping abandoned cropla…
View article: EGSDK-Net: Edge-Guided Stepwise Dual Kernel Update Network for Panoptic Segmentation
EGSDK-Net: Edge-Guided Stepwise Dual Kernel Update Network for Panoptic Segmentation Open
In recent years, panoptic segmentation has garnered increasing attention from researchers aiming to better understand scenes in images. Although many excellent studies have been proposed, they share some common unresolved issues. Firstly, …
View article: SRL‐ProtoNet: Self‐supervised representation learning for few‐shot remote sensing scene classification
SRL‐ProtoNet: Self‐supervised representation learning for few‐shot remote sensing scene classification Open
Using a deep learning method to classify a large amount of labelled remote sensing scene data produces good performance. However, it is challenging for deep learning based methods to generalise to classification tasks with limited data. Fe…
View article: Interpretable spatio-temporal modeling for soil temperature prediction
Interpretable spatio-temporal modeling for soil temperature prediction Open
Soil temperature (ST) is a crucial parameter in Earth system science. Accurate ST predictions provide invaluable insights; however, the “black box” nature of many deep learning approaches limits their interpretability. In this study, we pr…
View article: Enhanced Atrous Extractor and Self-Dynamic Gate Network for Superpixel Segmentation
Enhanced Atrous Extractor and Self-Dynamic Gate Network for Superpixel Segmentation Open
A superpixel is a group of pixels with similar low-level and mid-level properties, which can be seen as a basic unit in the pre-processing of remote sensing images. Therefore, superpixel segmentation can reduce the computation cost largely…
View article: FedQMIX: Communication-efficient federated learning via multi-agent reinforcement learning
FedQMIX: Communication-efficient federated learning via multi-agent reinforcement learning Open
Since the data samples on client devices are usually non-independent and non-identically distributed (non-IID), this will challenge the convergence of federated learning (FL) and reduce communication efficiency. This paper proposes FedQMIX…
View article: Decoupling with Entropy-based Equalization for Semi-Supervised Semantic Segmentation
Decoupling with Entropy-based Equalization for Semi-Supervised Semantic Segmentation Open
Semi-supervised semantic segmentation methods are the main solution to alleviate the problem of high annotation consumption in semantic segmentation. However, the class imbalance problem makes the model favor the head classes with sufficie…
View article: Lite‐weight semantic segmentation with AG self‐attention
Lite‐weight semantic segmentation with AG self‐attention Open
Due to the large computational and GPUs memory cost of semantic segmentation, some works focus on designing a lite weight model to achieve a good trade‐off between computational cost and accuracy. A common method is to combined CNN and vis…
View article: In-Season Crop Type Detection by Combing Sentinel-1A and Sentinel-2 Imagery Based on the CNN Model
In-Season Crop Type Detection by Combing Sentinel-1A and Sentinel-2 Imagery Based on the CNN Model Open
In-season crop-type maps are required for a variety of agricultural monitoring and decision-making applications. The earlier the crop type maps of the current growing season are obtained, the more beneficial it is for agricultural decision…
View article: To Fold or Not to Fold: a Necessary and Sufficient Condition on Batch-Normalization Layers Folding
To Fold or Not to Fold: a Necessary and Sufficient Condition on Batch-Normalization Layers Folding Open
Batch-Normalization (BN) layers have become fundamental components in the evermore complex deep neural network architectures. Such models require acceleration processes for deployment on edge devices. However, BN layers add computation bot…
View article: Blockchain-Enabled Joint Resource Allocation for Virtualized Video Service Functions
Blockchain-Enabled Joint Resource Allocation for Virtualized Video Service Functions Open
Power information is an important guarantee for energy security. As an important technical means of safety management and risk control, video monitoring is widely used in the power industry. Power video monitoring system uses efficient pro…
View article: A Personalized Task Allocation Strategy in Mobile Crowdsensing for Minimizing Total Cost
A Personalized Task Allocation Strategy in Mobile Crowdsensing for Minimizing Total Cost Open
Mobile crowdsensing utilizes the devices of a group of users to cooperatively perform some sensing tasks, where finding the perfect allocation from tasks to users is commonly crucial to guarantee task completion efficiency. However, existi…
View article: Mapping fallow fields using Sentinel-1 and Sentinel-2 archives over farming-pastoral ecotone of Northern China with Google Earth Engine
Mapping fallow fields using Sentinel-1 and Sentinel-2 archives over farming-pastoral ecotone of Northern China with Google Earth Engine Open
The cropland in the farming-pastoral ecotone of Northern China is highly unstable owing to environmental restoration projects, poor soil fertility, poverty, and rural labor loss, and it is characterized by a large number of fallow fields. …
View article: [Retracted] QoC‐Driven MEC Transfer System Framework in Wireless Networks
[Retracted] QoC‐Driven MEC Transfer System Framework in Wireless Networks Open
In this paper, we propose a Heterogeneous MEC System Framework based on Transfer Learning ( HMECSF-TL ), which uses convolutional neural network ( CNN ) to process few training samples. In view of the time‐varying network environment and t…
View article: Road crack detection network under noise based on feature pyramid structure with feature enhancement (road crack detection under noise)
Road crack detection network under noise based on feature pyramid structure with feature enhancement (road crack detection under noise) Open
Road crack detection is an important task for road safety and road maintenance. In the past, people made use of manual detection methods and tried to use computer vision to detect crack. The most prominent feature in recent years is the us…
View article: RAO‐UNet: a residual attention and octave UNet for road crack detection via balance loss
RAO‐UNet: a residual attention and octave UNet for road crack detection via balance loss Open
The acquisition and evaluation of road cracks are essential to ensure the availability of roads and necessary maintenance. However, the road cracks images have been obsessed with the problem of imbalance in the category and the number of c…
View article: TRS: Transformers for Remote Sensing Scene Classification
TRS: Transformers for Remote Sensing Scene Classification Open
Remote sensing scene classification remains challenging due to the complexity and variety of scenes. With the development of attention-based methods, Convolutional Neural Networks (CNNs) have achieved competitive performance in remote sens…
View article: Multiproxies Adaptive Distribution Loss with Weakly Supervised Feature Aggregation for Fine-Grained Retrieval
Multiproxies Adaptive Distribution Loss with Weakly Supervised Feature Aggregation for Fine-Grained Retrieval Open
Fine-grained retrieval is one of the complex problems in computer vision. Compared with general content-based image retrieval, fine-grained image retrieval faces more difficult challenges. In fine-grained image retrieval tasks, all classes…
View article: Ensemble Learning Based on Policy Optimization Neural Networks for Capability Assessment
Ensemble Learning Based on Policy Optimization Neural Networks for Capability Assessment Open
Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability asses…
View article: Evaluation of Five Deep Learning Models for Crop Type Mapping Using Sentinel-2 Time Series Images with Missing Information
Evaluation of Five Deep Learning Models for Crop Type Mapping Using Sentinel-2 Time Series Images with Missing Information Open
Accurate crop type maps play an important role in food security due to their widespread applicability. Optical time series data (TSD) have proven to be significant for crop type mapping. However, filling in missing information due to cloud…
View article: Ensemble Learning Based on Policy Optimization Neural Networks for Capability Assessment
Ensemble Learning Based on Policy Optimization Neural Networks for Capability Assessment Open
Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability asses…
View article: Toward Improving Image Retrieval via Global Saliency Weighted Feature
Toward Improving Image Retrieval via Global Saliency Weighted Feature Open
For full description of images’ semantic information, image retrieval tasks are increasingly using deep convolution features trained by neural networks. However, to form a compact feature representation, the obtained convolutional features…
View article: Comparison of Regional Winter Wheat Mapping Results from Different Similarity Measurement Indicators of NDVI Time Series and Their Optimized Thresholds
Comparison of Regional Winter Wheat Mapping Results from Different Similarity Measurement Indicators of NDVI Time Series and Their Optimized Thresholds Open
Generally, there is an inconsistency between the total regional crop area that was obtained from remote sensing technology and the official statistical data on crop areas. When performing scale conversion and data aggregation of remote sen…
View article: Multiple Time Series Perceptive Network for User Tag Suggestion in Online Innovation Community
Multiple Time Series Perceptive Network for User Tag Suggestion in Online Innovation Community Open
User tag suggestion technique, aiming at learning users' preferences over knowledge products from their historical behaviors, plays an important role in generating personalized recommendation in online innovation community. However, most c…
View article: A Nearly Optimal Method of Polar Code Constructions for the AWGN Channel
A Nearly Optimal Method of Polar Code Constructions for the AWGN Channel Open
Polar code is a kind of capacity-approaching code with explicit structure as part of the next generation wireless communication standard. The performance of the polar code is directly determined by the construction method, in which there a…
View article: Wise optimisation: deep image embedding by informative pair weighting and ranked list learning
Wise optimisation: deep image embedding by informative pair weighting and ranked list learning Open
Deep image embedding learns how to map images onto feature vectors. Image retrieval performance is often used to evaluate embedding quality. In this study, the authors proposed a wise deep image embedding optimisation (WDIEO) algorithm bas…