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Bihan Wen

Associate Professor

Nanyang Technological University (NTU)

Singapore

Research Interests

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Professors in Medical Imaging

About

Dr. Bihan Wen is an Assistant Professor at Nanyang Technological University in Singapore. His research primarily focuses on digital staining techniques, machine learning methodologies for time series forecasting, and advancements in photometric stereo and remote sensing. Recent publications highlight his contributions to knowledge distillation and efficient model designs in the context of image and data analysis.

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Collaborators (8)

Tong Ling

Nanyang Technological University (NTU)

SINGAPORE

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Xin Liu

Senior Researcher

Lappeenranta University of Technology

FINLAND

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Chen Zhang

Assistant Professor

The Hong Kong Polytechnic University

HONG KONG

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Heikki Kälviäinen

Professor of Computer Science and Engineering

Brno University of Technology

CZECH REPUBLIC

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Binbin Song

Associate Professor

Harbin Institute of Technology

CHINA

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Zhuotao Liu

Professor

Tsinghua University

CHINA

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Alex Kot

Nanyang Technological University (NTU)

SINGAPORE

View details

Huakun Li

Nanyang Technological University

SINGAPORE

View details

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Bihan Wen

Research Interests

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About

Articles (44)

A regularized deep self-expression feature augmentation network for few-shot unconstrained palmprint recognition

Confidence Matters: Balanced Pseudo-Label Selection for Semi-Supervised Few-Shot Learning

Single-Image Reflection Removal via Iterative Prompt Learning of Reflection Level

MSF-Mamba: Motion-Aware State Fusion Mamba for Efficient Micro-Gesture Recognition

Wavelength-scale noise-resistant on-chip spectrometer

WBCAtt+: Fine-grained pixel-level morphological annotations for white blood cell images

IL-DiffTSF: Invertible Latent Diffusion for Probabilistic Time Series Forecasting

AdaTrendLike: Adaptive Hierarchical Detrending and Trend Likelihood Scoring for Time-Series Anomaly Detection

Digital Staining With Knowledge Distillation: A Unified Framework for Unpaired and Paired-but-Misaligned Data

Digital Staining with Knowledge Distillation: A Unified Framework for Unpaired and Paired-But-Misaligned Data

A review of recent hybridized machine learning methodologies for time series forecasting on water-related variables

Revisiting One-Stage Deep Uncalibrated Photometric Stereo via Fourier Embedding

Revisiting One-stage Deep Uncalibrated Photometric Stereo via Fourier Embedding

DenseKD: Dense Knowledge Distillation by Exploiting Region and Sample Importance

DenseKD: Dense Knowledge Distillation by Exploiting Region and Sample Importance

WDTM-CL: Efficient Wavelet-based dual Transformer model with contrastive learning for spectral reconstruction from RGB images

ZoRI: Towards Discriminative Zero-Shot Remote Sensing Instance Segmentation

Heterogeneous Prototype Learning From Contaminated Faces Across Domains via Disentangling Latent Factors

Fast 3D localization of nano-objects in wide-field interferometric scattering microscopy via vectorial diffraction model-derived analytical fitting

DEEMO: De-identity Multimodal Emotion Recognition and Reasoning

Uncertainty-Aware Hyperspectral Image Reconstruction From RGB Measurements Using Unrolled Sparse Coding

Harnessing Forecast Uncertainty in Deep Learning for Time Series Anomaly Detection with Posterior Distribution Scoring

TWavefussion: Wavelet-based Diffusion with Transformer for Multivariate Time Series Anomaly Detection

Optimizing Sustainable Public Transport: A Graph Convolutional Model with Skip Connections for Passenger Volume Prediction

Structured residual sparsity for video compressive sensing reconstruction

Accelerated PALM for Nonconvex Low-rank Matrix Recovery with Theoretical Analysis

Cross-Image Disentanglement for Low-Light Enhancement in Real World

Leveraging Mixed Data Sources for Enhanced Road Segmentation in Synthetic Aperture Radar Images

Compressed Event Sensing (CES) Volumes for Event Cameras

Beyond Learned Metadata-Based Raw Image Reconstruction

Efficient Image Classification via Structured Low-Rank Matrix Factorization Regression

A joint learning method with consistency-aware for low-resolution facial expression recognition

Detection of Adversarial Attacks via Disentangling Natural Images and Perturbations

Two-Way Generation of High-Resolution EO and SAR Images via Dual Distortion-Adaptive GANs

Guided Adversarial Contrastive Distillation for Robust Students

Graph Neural Networks With Triple Attention for Few-Shot Learning

Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing: Nonlocal sparse and low-rank modeling

Physics-Driven Machine Learning for Computational Imaging [From the Guest Editor]

Towards Robust Image Denoising via Flow-based Joint Image and Noise Model

Purifying Low-light Images via Near-Infrared Enlightened Image

Real-time terahertz characterization for composite delamination using a lightweight CPU adaptive network

Targeted Universal Adversarial Examples for Remote Sensing

Learning to Solve Multiple-TSP With Time Window and Rejections via Deep Reinforcement Learning

Temporal Output Discrepancy for Loss Estimation-Based Active Learning

Collaborators (8)

Tong Ling

Xin Liu

Chen Zhang

Heikki Kälviäinen

Binbin Song

Zhuotao Liu

Alex Kot

Huakun Li

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