Search Results for author: Changhao Sun

Found 13 papers, 2 papers with code

OBBStacking: An Ensemble Method for Remote Sensing Object Detection

1 code implementation27 Sep 2022 Haoning Lin, Changhao Sun, Yunpeng Liu

Trying to address these problems, this paper proposes OBBStacking, an ensemble method that is compatible with OBBs and combines the detection results in a learned fashion.

Object object-detection +2

GasHisSDB: A New Gastric Histopathology Image Dataset for Computer Aided Diagnosis of Gastric Cancer

1 code implementation4 Jun 2021 Weiming Hu, Chen Li, Xiaoyan Li, Md Mamunur Rahaman, Jiquan Ma, Yong Zhang, HaoYuan Chen, Wanli Liu, Changhao Sun, YuDong Yao, Hongzan Sun, Marcin Grzegorzek

In order to prove that the methods of different periods in the field of image classification have discrepancies on GasHisSDB, we select a variety of classifiers for evaluation.

BIG-bench Machine Learning Image Classification +1

GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection

no code implementations29 Apr 2021 HaoYuan Chen, Chen Li, Ge Wang, Xiaoyan Li, Md Rahaman, Hongzan Sun, Weiming Hu, Yixin Li, Wanli Liu, Changhao Sun, Shiliang Ai, Marcin Grzegorzek

In this paper, a multi-scale visual transformer model, referred as GasHis-Transformer, is proposed for Gastric Histopathological Image Detection (GHID), which enables the automatic global detection of gastric cancer images.

Adversarial Attack General Classification +3

Study on MCS Selection and Spectrum Allocation for URLLC Traffic under Delay and Reliability Constraint in 5G Network

no code implementations6 Jan 2021 Yuehong Gao, Changhao Sun, Xiaonan Zhang, Xiao Hong

Theoretical results in the scenario of a 5G New Radio system are presented, where the SNR thresholds for adaptive modulation and coding scheme selection, transmission rate and delay, as well as admission region under different configurations are discussed.

A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis

no code implementations29 Sep 2020 Yixin Li, Chen Li, Xiaoyan Li, Kai Wang, Md Mamunur Rahaman, Changhao Sun, Hao Chen, Xinran Wu, Hong Zhang, Qian Wang

In this review, we present a comprehensive overview of pathology image analysis based on the markov random fields (MRFs) and conditional random fields (CRFs), which are two popular random field models.

A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentation

no code implementations8 Mar 2020 Jinghua Zhang, Chen Li, Frank Kulwa, Xin Zhao, Changhao Sun, Zihan Li, Tao Jiang, Hong Li

In order to assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multi-scale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper.

Image Segmentation Segmentation +1

Gastric histopathology image segmentation using a hierarchical conditional random field

no code implementations3 Mar 2020 Changhao Sun, Chen Li, Jinghua Zhang, Muhammad Rahaman, Shiliang Ai, Hao Chen, Frank Kulwa, Yixin Li, Xiaoyan Li, Tao Jiang

This HCRF model is built up with higher order potentials, including pixel-level and patch-level potentials, and graph-based post-processing is applied to further improve its segmentation performance.

Image Segmentation Segmentation +2

Stochastic Model Pruning via Weight Dropping Away and Back

no code implementations5 Dec 2018 Haipeng Jia, Xueshuang Xiang, Da Fan, Meiyu Huang, Changhao Sun, Yang He

Addressing these two issues, this paper proposes the Drop Pruning approach, which leverages stochastic optimization in the pruning process by introducing a drop strategy at each pruning step, namely, drop away, which stochastically deletes some unimportant weights, and drop back, which stochastically recovers some pruned weights.

Model Compression Stochastic Optimization

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