Publications (12)
Optical biomarker of metabolism for breast tumor diagnosis: Insights from subcellular dynamics
Zichen Yin, Shuwei Zhang, Bin He +10
Label-free metabolic dynamics contrast is highly appealing but difficult to achieve in biomedical imaging. Interference offers a highly sensitive mechanism for capturing the metabo…
AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks
Jingfei Chang, Yang Lu, Ping Xue +2
With the increase of structure complexity, convolutional neural networks (CNNs) take a fair amount of computation cost. Meanwhile, existing research reveals the salient parameter r…
IR2Net: Information Restriction and Information Recovery for Accurate Binary Neural Networks
Ping Xue, Yang Lu, Jingfei Chang +2
Weight and activation binarization can efficiently compress deep neural networks and accelerate model inference, but cause severe accuracy degradation. Existing optimization method…
UCP: Uniform Channel Pruning for Deep Convolutional Neural Networks Compression and Acceleration
Jingfei Chang, Yang Lu, Ping Xue +2
To apply deep CNNs to mobile terminals and portable devices, many scholars have recently worked on the compressing and accelerating deep convolutional neural networks. Based on thi…
Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction
Haoyu Zhou, Ping Xue, Hao Zhang +1
Deploying 3D graph neural networks (GNNs) that are equivariant to 3D rotations (the group SO(3)) on edge devices is challenging due to their high computational cost. This paper add…
ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN
Jingfei Chang, Yang Lu, Ping Xue +2
As the convolutional neural network (CNN) gets deeper and wider in recent years, the requirements for the amount of data and hardware resources have gradually increased. Meanwhile,…
Preserving Continuous Symmetry in Discrete Spaces: Geometric-Aware Quantization for SO(3)-Equivariant GNNs
Haoyu Zhou, Ping Xue, Hao Zhang +1
Equivariant Graph Neural Networks (GNNs) are essential for physically consistent molecular simulations but suffer from high computational costs and memory bottlenecks, especially w…
Evolution of the number and temperature of the remaining cold atoms in CW-laser photoionization of laser-cooled Rb atoms
Fei Wang, Feng-Dong Jia, Wei-Chen Liang +11
Based on the Rb-Rb hybrid trap, we investigate the effect of ion-atom elastic collisions on the number and temperature of the remaining atoms. We measured the remaining atomic…
First-in-human spinal cord tumor imaging with fast adaptive focus tracking robotic-OCT
Bin He, Yuzhe Ying, Yejiong Shi +14
Current surgical procedures for spinal cord tumors lack in vivo high-resolution, high-speed multifunctional imaging systems, posing challenges for precise tumor resection and intra…
Generation of cold polyatomic cations by cascade reactive two-body ion-atom collisions
Wei-Chen Liang, Feng-Dong Jia, Fei Wang +8
Polyatomic cations Rb ( = 2, 3,) have been produced by cascade two-body ion-atom reactive collisions in the two-step CW-laser photoionization of laser-coole…
Self-Distribution Binary Neural Networks
Ping Xue, Yang Lu, Jingfei Chang +2
In this work, we study the binary neural networks (BNNs) of which both the weights and activations are binary (i.e., 1-bit representation). Feature representation is critical for d…
Fast and label-free 3D virtual H&E histology via active modulation-assisted dynamic full-field OCT
Zichen Yin, Bin He, Yuzhe Ying +10
Pathological features are the gold standard for tumor diagnosis, guiding treatment and prognosis. However, standard histopathological process is labor-intensive and time-consuming,…