Jiangyun Li
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View article: Symmetry Alignment–Feature Interaction Network for Human Ear Similarity Detection and Authentication
Symmetry Alignment–Feature Interaction Network for Human Ear Similarity Detection and Authentication Open
In the context of ear-based biometric identity authentication, symmetry between the left and right ears emerges as a pivotal factor, particularly when registration involves one ear and authentication utilizes its contralateral counterpart.…
View article: Referring Remote Sensing Image Segmentation via Bidirectional Alignment Guided Joint Prediction
Referring Remote Sensing Image Segmentation via Bidirectional Alignment Guided Joint Prediction Open
Referring Remote Sensing Image Segmentation (RRSIS) is critical for ecological monitoring, urban planning, and disaster management, requiring precise segmentation of objects in remote sensing imagery guided by textual descriptions. This ta…
View article: DVR: Towards Accurate Hyperspectral Image Classifier via Discrete Vector Representation
DVR: Towards Accurate Hyperspectral Image Classifier via Discrete Vector Representation Open
In recent years, convolutional neural network (CNN)-based and transformer-based approaches have made strides in improving the performance of hyperspectral image (HSI) classification tasks. However, misclassifications are unavoidable in the…
View article: Enhancing Semantic Information Representation in Multi‐View Geo‐Localization through Dual‐Branch Network with Feature Consistency Enhancement and Multi‐Level Feature Mining
Enhancing Semantic Information Representation in Multi‐View Geo‐Localization through Dual‐Branch Network with Feature Consistency Enhancement and Multi‐Level Feature Mining Open
Metric learning is fundamental to multi‐view geo‐localization, as it aims to establish a distance metric that minimizes the feature space distance between similar data points while maximizing the separation between dissimilar ones. However…
View article: FAHM: Frequency-Aware Hierarchical Mamba for Hyperspectral Image Classification
FAHM: Frequency-Aware Hierarchical Mamba for Hyperspectral Image Classification Open
Convolutional neural networks and Transformers have garnered substantial attention in hyperspectral image (HSI) classification, and recently Mamba has made significant progress in modeling long sequences. However, existing Mamba-based appr…
View article: Smart Ship Draft Reading by Dual-Flow Deep Learning Architecture and Multispectral Information
Smart Ship Draft Reading by Dual-Flow Deep Learning Architecture and Multispectral Information Open
In maritime transportation, a ship’s draft survey serves as a primary method for weighing bulk cargo. The accuracy of the ship’s draft reading determines the fairness of bulk cargo transactions. Human visual-based draft reading methods fac…
View article: Adaptive FSS: A Novel Few-Shot Segmentation Framework via Prototype Enhancement
Adaptive FSS: A Novel Few-Shot Segmentation Framework via Prototype Enhancement Open
The Few-Shot Segmentation (FSS) aims to accomplish the novel class segmentation task with a few annotated images. Current FSS research based on meta-learning focuses on designing a complex interaction mechanism between the query and suppor…
View article: A review of remote sensing image segmentation by deep learning methods
A review of remote sensing image segmentation by deep learning methods Open
Remote sensing (RS) images enable high-resolution information collection from complex ground objects and are increasingly utilized in the earth observation research. Recently, RS technologies are continuously enhanced by various characteri…
View article: Med-DANet V2: A Flexible Dynamic Architecture for Efficient Medical Volumetric Segmentation
Med-DANet V2: A Flexible Dynamic Architecture for Efficient Medical Volumetric Segmentation Open
Recent works have shown that the computational efficiency of 3D medical image (e.g. CT and MRI) segmentation can be impressively improved by dynamic inference based on slice-wise complexity. As a pioneering work, a dynamic architecture net…
View article: UCTNet with Dual-Flow Architecture: Snow Coverage Mapping with Sentinel-2 Satellite Imagery
UCTNet with Dual-Flow Architecture: Snow Coverage Mapping with Sentinel-2 Satellite Imagery Open
Satellite remote sensing (RS) has been drawing considerable research interest in land-cover classification due to its low price, short revisit time, and large coverage. However, clouds pose a significant challenge, occluding the objects on…
View article: CM-MaskSD: Cross-Modality Masked Self-Distillation for Referring Image Segmentation
CM-MaskSD: Cross-Modality Masked Self-Distillation for Referring Image Segmentation Open
Referring image segmentation (RIS) is a fundamental vision-language task that intends to segment a desired object from an image based on a given natural language expression. Due to the essentially distinct data properties between image and…
View article: Med-Tuning: A New Parameter-Efficient Tuning Framework for Medical Volumetric Segmentation
Med-Tuning: A New Parameter-Efficient Tuning Framework for Medical Volumetric Segmentation Open
The "pre-training then fine-tuning (FT)" paradigm is widely adopted to boost the model performance of deep learning-based methods for medical volumetric segmentation. However, conventional full FT incurs high computational and memory costs…
View article: FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation
FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation Open
The research community has witnessed the powerful potential of self-supervised Masked Image Modeling (MIM), which enables the models capable of learning visual representation from unlabeled data. In this paper, to incorporate both the cruc…
View article: MF2-MVQA: A Multi-stage Feature Fusion method for Medical Visual Question Answering
MF2-MVQA: A Multi-stage Feature Fusion method for Medical Visual Question Answering Open
There is a key problem in the medical visual question answering task that how to effectively realize the feature fusion of language and medical images with limited datasets. In order to better utilize multi-scale information of medical ima…
View article: Hyper-LGNet: Coupling Local and Global Features for Hyperspectral Image Classification
Hyper-LGNet: Coupling Local and Global Features for Hyperspectral Image Classification Open
Hyperspectral sensors provide an opportunity to capture the intensity of high spatial/spectral information and enable applications for high-level earth observation missions, such as accurate land cover mapping and target/object detection. …
View article: Hyper-ES2T: Efficient Spatial–Spectral Transformer for the classification of hyperspectral remote sensing images
Hyper-ES2T: Efficient Spatial–Spectral Transformer for the classification of hyperspectral remote sensing images Open
In recent years, convolutional neural networks have continuously dominated the downstream tasks on hyperspectral remote sensing images with its strong local feature extraction capability. However, convolution operations cannot effectively …
View article: Positive-Negative Equal Contrastive Loss for Semantic Segmentation
Positive-Negative Equal Contrastive Loss for Semantic Segmentation Open
The contextual information is critical for various computer vision tasks, previous works commonly design plug-and-play modules and structural losses to effectively extract and aggregate the global context. These methods utilize fine-label …
View article: Med-DANet: Dynamic Architecture Network for Efficient Medical Volumetric Segmentation
Med-DANet: Dynamic Architecture Network for Efficient Medical Volumetric Segmentation Open
For 3D medical image (e.g. CT and MRI) segmentation, the difficulty of segmenting each slice in a clinical case varies greatly. Previous research on volumetric medical image segmentation in a slice-by-slice manner conventionally use the id…
View article: CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of Remote Sensing Images
CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of Remote Sensing Images Open
Semantic segmentation by using remote sensing images is an efficient method for agricultural crop classification. Recent solutions in crop segmentation are mainly deep-learning-based methods, including two mainstream architectures: Convolu…
View article: Category guided attention network for brain tumor segmentation in MRI
Category guided attention network for brain tumor segmentation in MRI Open
Objective . Magnetic resonance imaging (MRI) has been widely used for the analysis and diagnosis of brain diseases. Accurate and automatic brain tumor segmentation is of paramount importance for radiation treatment. However, low tissue con…
View article: Wheat Canopy Cover Estimation by Optimized Random Forest and UAV Multispectral imagery
Wheat Canopy Cover Estimation by Optimized Random Forest and UAV Multispectral imagery Open
Canopy cover estimation is widely applied to reflect crop status in agriculture research and management. In particular, an accurate CC estimation is beneficial for crop model calibration, providing high-accuracy observations. Recent soluti…
View article: TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images
TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images Open
Transformer, benefiting from global (long-range) information modeling using self-attention mechanism, has been successful in natural language processing and computer vision recently. Convolutional Neural Networks, capable of capturing loca…
View article: Attention Guided Global Enhancement and Local Refinement Network for Semantic Segmentation
Attention Guided Global Enhancement and Local Refinement Network for Semantic Segmentation Open
The encoder-decoder architecture is widely used as a lightweight semantic segmentation network. However, it struggles with a limited performance compared to a well-designed Dilated-FCN model for two major problems. First, commonly used ups…
View article: Ir-UNet: Irregular Segmentation U-Shape Network for Wheat Yellow Rust Detection by UAV Multispectral Imagery
Ir-UNet: Irregular Segmentation U-Shape Network for Wheat Yellow Rust Detection by UAV Multispectral Imagery Open
Crop disease is widely considered as one of the most pressing challenges for food crops, and therefore an accurate crop disease detection algorithm is highly desirable for its sustainable management. The recent use of remote sensing and de…
View article: Efficient Transformer for Remote Sensing Image Segmentation
Efficient Transformer for Remote Sensing Image Segmentation Open
Semantic segmentation for remote sensing images (RSIs) is widely applied in geological surveys, urban resources management, and disaster monitoring. Recent solutions on remote sensing segmentation tasks are generally addressed by CNN-based…
View article: TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer Open
Transformer, which can benefit from global (long-range) information modeling using self-attention mechanisms, has been successful in natural language processing and 2D image classification recently. However, both local and global features …
View article: Sentinel-2 Satellite Imagery for Urban Land Cover Classification by Optimized Random Forest Classifier
Sentinel-2 Satellite Imagery for Urban Land Cover Classification by Optimized Random Forest Classifier Open
Land cover classification is able to reflect the potential natural and social process in urban development, providing vital information to stakeholders. Recent solutions on land cover classification are generally addressed by remotely sens…
View article: Image‐Based Iron Slag Segmentation via Graph Convolutional Networks
Image‐Based Iron Slag Segmentation via Graph Convolutional Networks Open
Slagging‐off (i.e., slag removal) is an important preprocessing operation of steel‐making to improve the purity of iron. Current manual‐operated slag removal schemes are inefficient and labor‐intensive. Automatic slagging‐off is desirable …