activity
20202026
most citedA Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution

59 citations · 174 across the 18 of their papers we have counts for

collaborators

20 papers

cs.NE2026

Beyond the Hamming Cliff: Compact Spatial Encodings Preserving Semantic Distance in Spiking Neural Networks

Sergio Davies, Muhammad Aitsam, Morgan-Tyler Stone +2

By pre-processing input signals with Gray, Thermometer, Johnson and hybrid encodings before passing them to spiking neural networks running on SpiNNaker hardware, Davies et al.(202…

cs.LG2026

LDAC-Net: A Learnable Multi-Lag Differencing Attention-Convolution Network for Drift-Robust Recognition with Low-Cost MOX Gas Sensors

Xin Zhang, Liangxiu Han, Yue Shi +1

Portable electronic-nose systems based on low-cost metal-oxide (MOX) gas sensors offer a practical solution for gas and odour recognition, but their signals are affected by slow ch…

cs.CV2026

Physics Closure Matters for Machine Olfaction: A Maxwell-Stefan Graph Solver for Identifiable Dynamic Gas Unmixing

Yue Shi, Liangxiu Han, Xin Zhang +1

Machine olfaction for gas unmixing is an underconstrained inverse problem in which gas compositions must be inferred from low-dimensional, delayed, and entangled sensor responses p…

cs.CV2026

A WDLoRA-Based Multimodal Generative Framework for Clinically Guided Corneal Confocal Microscopy Image Synthesis in Diabetic Neuropathy

Xin Zhang, Liangxiu Han, Tam Sobeih +5

Corneal Confocal Microscopy (CCM) is a sensitive tool for assessing small-fiber damage in Diabetic Peripheral Neuropathy (DPN), yet the development of robust, automated deep learni…

cs.AI2026

AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction Under Water Stress

Yue Shi, Liangxiu Han, Xin Zhang +7

Accurate prediction of crop above-ground biomass (AGB) under water stress is critical for monitoring crop productivity, guiding irrigation, and supporting climate-resilient agricul…

cs.CV2025

A Novel Large Vision Foundation Model (LVFM)-based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management

Shen Tan, Xin Zhang, Liangxiu Han +2

Accurate, cost-effective monitoring of plantation aboveground biomass (AGB) is crucial for supporting local livelihoods and carbon sequestration initiatives like the China Certifie…

cs.CV2025

HMSViT: A Hierarchical Masked Self-Supervised Vision Transformer for Corneal Nerve Segmentation and Diabetic Neuropathy Diagnosis

Xin Zhang, Liangxiu Han, Yue Shi +4

Diabetic Peripheral Neuropathy (DPN) affects nearly half of diabetes patients, requiring early detection. Corneal Confocal Microscopy (CCM) enables non-invasive diagnosis, but auto…

cs.LG2025★ 5 cited

Deep Learning Meets Process-Based Models: A Hybrid Approach to Agricultural Challenges

Yue Shi, Liangxiu Han, Xin Zhang +7

Process-based models (PBMs) and deep learning (DL) are two key approaches in agricultural modelling, each offering distinct advantages and limitations. PBMs provide mechanistic ins…

cs.AI2025

TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration

Xin Zhang, Liangxiu Han, Stephen White +5

Acute Coronary Syndromes (ACS), including ST-segment elevation myocardial infarctions (STEMI) and non-ST-segment elevation myocardial infarctions (NSTEMI), remain a leading cause o…

eess.IV2024

WaveDiffUR: A diffusion SDE-based solver for ultra magnification super-resolution in remote sensing images

Yue Shi, Liangxiu Han, Darren Dancy +1

Deep neural networks have recently achieved significant advancements in remote sensing superresolu-tion (SR). However, most existing methods are limited to low magnification rates…

cs.CV2024★ 1 cited

A Novel Spike Transformer Network for Depth Estimation from Event Cameras via Cross-modality Knowledge Distillation

Xin Zhang, Liangxiu Han, Tam Sobeih +2

Depth estimation is a critical task in computer vision, with applications in autonomous navigation, robotics, and augmented reality. Event cameras, which encode temporal changes in…

cs.CV2023

A Fast Fourier Convolutional Deep Neural Network For Accurate and Explainable Discrimination Of Wheat Yellow Rust And Nitrogen Deficiency From Sentinel-2 Time-Series Data

Yue Shi, Liangxiu Han, Pablo González-Moreno +7

Accurate and timely detection of plant stress is essential for yield protection, allowing better-targeted intervention strategies. Recent advances in remote sensing and deep learni…

cs.CV2023★ 15 cited

A generic self-supervised learning (SSL) framework for representation learning from spectra-spatial feature of unlabeled remote sensing imagery

Xin Zhang, Liangxiu Han

Remote sensing data has been widely used for various Earth Observation (EO) missions such as land use and cover classification, weather forecasting, agricultural management, and en…

cs.DC2023★ 1 cited

A Generic Performance Model for Deep Learning in a Distributed Environment

Tulasi Kavarakuntla, Liangxiu Han, Huw Lloyd +3

Performance modelling of a deep learning application is essential to improve and quantify the efficiency of the model framework. However, existing performance models are mostly cas…

eess.IV2023★ 31 cited

sMRI-PatchNet: A novel explainable patch-based deep learning network for Alzheimer's disease diagnosis and discriminative atrophy localisation with Structural MRI

Xin Zhang, Liangxiu Han, Lianghao Han +3

Structural magnetic resonance imaging (sMRI) can identify subtle brain changes due to its high contrast for soft tissues and high spatial resolution. It has been widely used in dia…

cs.DC2022

Layer-Wise Partitioning and Merging for Efficient and Scalable Deep Learning

Samson B. Akintoye, Liangxiu Han, Huw Lloyd +4

Deep Neural Network (DNN) models are usually trained sequentially from one layer to another, which causes forward, backward and update locking's problems, leading to poor performan…

eess.IV2021★ 59 cited

A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution

Yue Shi, Liangxiu Han, Lianghao Han +3

Realistic hyperspectral image (HSI) super-resolution (SR) techniques aim to generate a high-resolution (HR) HSI with higher spectral and spatial fidelity from its low-resolution (L…

cs.CV2021★ 1 cited

The self-supervised spectral-spatial attention-based transformer network for automated, accurate prediction of crop nitrogen status from UAV imagery

Xin Zhang, Liangxiu Han, Tam Sobeih +4

Nitrogen (N) fertilizer is routinely applied by farmers to increase crop yields. At present, farmers often over-apply N fertilizer in some locations or at certain times because the…

eess.IV2021★ 43 cited

CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Images

Xin Zhang, Liangxiu Han, Tam Sobeih +6

Accurate and rapid detection of COVID-19 pneumonia is crucial for optimal patient treatment. Chest X-Ray (CXR) is the first line imaging test for COVID-19 pneumonia diagnosis as it…

cs.CV2020★ 18 cited

A Biologically Interpretable Two-stage Deep Neural Network (BIT-DNN) For Vegetation Recognition From Hyperspectral Imagery

Yue Shi, Liangxiu Han, Wenjiang Huang +4

Spectral-spatial based deep learning models have recently proven to be effective in hyperspectral image (HSI) classification for various earth monitoring applications such as land…