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Claim this profileWorks229 from public data
- A framework of blockchain-based secure and privacy-preserving E-government system189
A framework of a decentralized e-government peer-to-peer (p2p) system using the blockchain technology is proposed, which can ensure both information security and privacy while simultaneously increasing the trust of the public sectors.
- Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network161
A deep recurrent neural network (RNN) with a sliding window cropping strategy (SWCS) to signal classification of MI-BCIs is applied, and the proposed GRU-RNN architecture achieves the lowest misclassification rates on all BCI benchmark datasets.
- Meta Architecture for Point Cloud Analysis115
This paper takes the initiative to explore and propose a unified framework called PointMeta, to which the popular 3D point cloud analysis approaches could fit, and shows very strong performance in efficiency and effectiveness through extensive experiments on challenging benchmarks, and verifies the necessity and benefits of high-level interpretation, contrast, and comparison like PointMeta.
- DiffRate : Differentiable Compression Rate for Efficient Vision Transformers110
Differentiable Compression Rate (DiffRate), a novel token compression method that has several appealing properties prior arts do not have, is proposed and achieves state-of-the-art performance.
- Towards Compact CNNs via Collaborative Compression105
A Collaborative Compression scheme, which joints channel pruning and tensor decomposition to compress CNN models by simultaneously learning the model sparsity and low-rankness and proposes multi-step heuristic compression to remove redundant compression units step-by-step.
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- AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration94
This work designs a unified search space that consists of all possible time steps and various architectures and introduces a two stage evolutionary algorithm to find the optimal solution in the designed search space.
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- AffineQuant: Affine Transformation Quantization for Large Language Models72
This paper advocates for the direct optimization using equivalent Affine transformations in PTQ (AffineQuant) using the corresponding inverse matrix to ensure equivalence between the pre- and post-quantization outputs of PTQ, thereby maintaining its efficiency and generalization capabilities.
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- Staged Competence Learning in Developmental Robotics70
An approach towards developmental growth for robotics that utilizes natural constraints in a general learning mechanism that is applicable to all levels of control and behavior, and can be implemented in any robotic configuration.
- Machine Learning Algorithms for Network Intrusion Detection64
This chapter systematically reviews two groups of common intrusion detection systems using fuzzy logic and artificial neural networks, and evaluates them by utilizing the widely used KDD 99 benchmark dataset.
- Low-Cost Inertial Measurement Unit Calibration With Nonlinear Scale Factors59
The errors of acceleration and angular velocity led by the algorithm are significantly smaller than those resulted from the existing approaches using the same testing data sets, demonstrating a remarkable improvement of 64.12% and 47.90%, respectively.
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- 1xN Pattern for Pruning Convolutional Neural Networks54
This paper proposes a novel 1×N pruning pattern that prunes consecutive N output kernels with the same input channel index into one block, which serves as a basic pruning granularity of thisPruning pattern.
- Feature grouping and selection: A graph-based approach53
A general framework based on graph processing and three-way mutual information metrics is proposed in this paper that works by clustering similar features into groups, from which representative features are then drawn and two different feature selection techniques are presented.
- A robot calligraphy system: From simple to complex writing by human gestures51
A robot calligraphy system that firstly applies human arm gestures to establish a font database of Chinese character elementary strokes and English letters, then uses the created database and human gestures to write Chinese characters and English words.
- Self-Organizing Brain Emotional Learning Controller Network for Intelligent Control System of Mobile Robots50
The comparative study using the cutting-edge neural network-based control systems confirms that the proposed network is capable of producing better control performances with high computational efficiency.
- Use of human gestures for controlling a mobile robot via adaptive CMAC network and fuzzy logic controller44
A system which uses human gestures to control an autonomous mobile robot integrating a manipulator and a video surveillance platform, which is able to conveniently control a mobile robot using virtual driving method, with smooth manoeuvring trajectories in various speeds.
- A developmental algorithm for ocular–motor coordination44
A model of ocular-motor development, inspired by ideas and data from developmental psychology, is presented, which is simple, extremely fast, self-calibrating, adaptive to change, and exhibits emergent stages of behaviour as learning progresses.
- Training Compact CNNs for Image Classification Using Dynamic-Coded Filter Fusion41
This paper presents a novel filter pruning method, dubbed dynamic-coded filter fusion (DCFF), to derive compact CNNs in a computation-economical and regularization-free manner for efficient image classification.
- Developmental learning for autonomous robots40
Ideas and inspiration from early infant psychology are used to examine how robot systems could discover the structure of their local sensory-motor spaces and learn how to coordinate these for the control of action.
- A Secure and Privacy-Preserving E-Government Framework Using Blockchain and Artificial Immunity39
The experimental results show the efficacy of the proposed framework in that it can mitigate insider and external threats in e-Government systems whilst simultaneously preserving the privacy of information.
- Learning Efficient GANs for Image Translation via Differentiable Masks and Co-Attention Distillation38
A novel GAN compression method, termed DMAD, is introduced by proposing a Differentiable Mask and a co-attention Distillation that simultaneously distills informative attention maps from both the generator and discriminator of a pre-trained model to the searched generator, effectively stabilizing the adversarial training of the light-weight model.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-16. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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