Search Results for author: Xiaobo Liu

Found 13 papers, 7 papers with code

Proprioceptive Learning with Soft Polyhedral Networks

no code implementations16 Aug 2023 Xiaobo Liu, Xudong Han, Wei Hong, Fang Wan, Chaoyang Song

Proprioception is the "sixth sense" that detects limb postures with motor neurons.

Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps

no code implementations16 Aug 2022 Kun Qiu, Harry Chang, Ying Wang, Xiahui Yu, Wenjun Zhu, Yingqi Liu, Jianwei Ma, Weigang Li, Xiaobo Liu, Shuo Dai

Sophisticated traffic analytics, such as the encrypted traffic analytics and unknown malware detection, emphasizes the need for advanced methods to analyze the network traffic.

Malware Detection Traffic Classification

Large-Scale Hyperspectral Image Clustering Using Contrastive Learning

1 code implementation15 Nov 2021 Yaoming Cai, Zijia Zhang, Yan Liu, Pedram Ghamisi, Kun Li, Xiaobo Liu, Zhihua Cai

Specifically, we exploit a symmetric twin neural network comprised of a projection head with a dimensionality of the cluster number to conduct dual contrastive learning from a spectral-spatial augmentation pool.

Clustering Contrastive Learning +2

Fully Linear Graph Convolutional Networks for Semi-Supervised Learning and Clustering

1 code implementation15 Nov 2021 Yaoming Cai, Zijia Zhang, Zhihua Cai, Xiaobo Liu, Yao Ding, Pedram Ghamisi

This paper presents FLGC, a simple yet effective fully linear graph convolutional network for semi-supervised and unsupervised learning.

Clustering Computational Efficiency

Weighted Ensemble-model and Network Analysis: A method to predict fluid intelligence via naturalistic functional connectivity

no code implementations6 Jan 2021 Xiaobo Liu, Su Yang

Methods: In this study, inspired by multi-layer brain network structure, we propose a new method namely Weighted Ensemble-model and Network Analysis, which combines the machine learning and graph theory for improved fluid intelligence prediction.

BIG-bench Machine Learning regression

DeepClaw: A Robotic Hardware Benchmarking Platform for Learning Object Manipulation

2 code implementations6 May 2020 Fang Wan, Haokun Wang, Xiaobo Liu, Linhan Yang, Chaoyang Song

We present benchmarking results of the DeepClaw system for a baseline Tic-Tac-Toe task, a bin-clearing task, and a jigsaw puzzle task using three sets of standard robotic hardware.


Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral Image

1 code implementation22 Apr 2020 Yaoming Cai, Zijia Zhang, Zhihua Cai, Xiaobo Liu, Xinwei Jiang, Qin Yan

In this paper, we revisit the subspace clustering with graph convolution and present a novel subspace clustering framework called Graph Convolutional Subspace Clustering (GCSC) for robust HSI clustering.

Clustering Graph Embedding

Rigid-Soft Interactive Learning for Robust Grasping

2 code implementations29 Feb 2020 Linhan Yang, Fang Wan, Haokun Wang, Xiaobo Liu, Yujia Liu, Jia Pan, Chaoyang Song

We use soft, stuffed toys for training, instead of everyday objects, to reduce the integration complexity and computational burden and exploit such rigid-soft interaction by changing the gripper fingers to the soft ones when dealing with rigid, daily-life items such as the Yale-CMU-Berkeley (YCB) objects.

Small Data Image Classification Test

Multi-PCA based Fault Detection Model Combined with Prior knowledge of HVAC

no code implementations21 Nov 2019 Ziming Liu, Xiaobo Liu

The traditional PCA fault detection methods completely depend on the training data.

Fault Detection

BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image

2 code implementations17 Apr 2019 Yaoming Cai, Xiaobo Liu, Zhihua Cai

The framework consists of a band attention module (BAM), which aims to explicitly model the nonlinear inter-dependencies between spectral bands, and a reconstruction network (RecNet), which is used to restore the original HSI cube from the learned informative bands, resulting in a flexible architecture.

Hyperspectral Image Classification

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