Search Results for author: Lin Cheng

Found 14 papers, 2 papers with code

Graph Attention-Based Symmetry Constraint Extraction for Analog Circuits

no code implementations22 Dec 2023 Qi Xu, Lijie Wang, Jing Wang, Song Chen, Lin Cheng, Yi Kang

In recent years, analog circuits have received extensive attention and are widely used in many emerging applications.

Graph Attention

Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Images

no code implementations15 Nov 2023 Zhaocong liu, Fa Zhang, Lin Cheng, Huanxi Deng, Xiaoyan Yang, Zhenyu Zhang, ChiChun Zhou

Addressing this, an unsupervised classification method with three key ideas is introduced: 1) dual-step feature dimensionality reduction using a pre-trained model and manifold learning, 2) a voting mechanism from multiple clustering algorithms, and 3) post-hoc instead of prior manual annotation.

Classification Dimensionality Reduction +1

All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation

1 code implementation8 Aug 2023 Weixuan Sun, Yanhao Zhang, Zhen Qin, Zheyuan Liu, Lin Cheng, Fanyi Wang, Yiran Zhong, Nick Barnes

Given a pair of augmented views, our approach regularizes the activation intensities between a pair of augmented views, while also ensuring that the affinity across regions within each view remains consistent.

Object Localization Weakly supervised Semantic Segmentation +1

Risk Assessment with Generic Energy Storage under Exogenous and Endogenous Uncertainty

no code implementations26 Mar 2022 Ning Qi, Lin Cheng, Yuxiang Wan, Yingrui Zhuang, Zeyu Liu

Current risk assessment ignores the stochastic nature of energy storage availability itself and thus lead to potential risk during operation.

Reinforcement Learning for Standards Design

no code implementations13 Oct 2021 Shahrukh Khan Kasi, Sayandev Mukherjee, Lin Cheng, Bernardo A. Huberman

Communications standards are designed via committees of humans holding repeated meetings over months or even years until consensus is achieved.

reinforcement-learning Reinforcement Learning (RL)

TSGB: Target-Selective Gradient Backprop for Probing CNN Visual Saliency

1 code implementation11 Oct 2021 Lin Cheng, Pengfei Fang, Yanjie Liang, Liao Zhang, Chunhua Shen, Hanzi Wang

Inspired by those observations, we propose a novel visual saliency method, termed Target-Selective Gradient Backprop (TSGB), which leverages rectification operations to effectively emphasize target classes and further efficiently propagate the saliency to the image space, thereby generating target-selective and fine-grained saliency maps.

GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts

no code implementations11 Nov 2020 Lin Cheng, Zijiang Yang

Program synthesis is the task to automatically generate programs based on user specification.

Program Synthesis

Exploring the parameter reusability of CNN

no code implementations8 Aug 2020 Wei Wang, Lin Cheng, Yanjie Zhu, Dong Liang

In recent times, using small data to train networks has become a hot topic in the field of deep learning.

Semantic Segmentation Transfer Learning

Learning Object Scale With Click Supervision for Object Detection

no code implementations20 Feb 2020 Liao Zhang, Yan Yan, Lin Cheng, Hanzi Wang

Finally, we fuse these CAMs together to generate pseudoground-truths and train a fully-supervised object detector withthese ground-truths.

Object object-detection +1

Hallucinated Adversarial Learning for Robust Visual Tracking

no code implementations17 Jun 2019 Qiangqiang Wu, Zhihui Chen, Lin Cheng, Yan Yan, Bo Li, Hanzi Wang

Incorporating such an ability to hallucinate diverse new samples of the tracked instance can help the trackers alleviate the over-fitting problem in the low-data tracking regime.

Visual Tracking

A Novel Self-Intersection Penalty Term for Statistical Body Shape Models and Its Applications in 3D Pose Estimation

no code implementations24 Jan 2019 Zaiqiang Wu, Wei Jiang, Hao Luo, Lin Cheng

To calculate the partial derivatives with respect to the coordinates of the vertices, we employed detection rays to divide vertices of statistical body shape models into different groups depending on whether the vertex is in the region of self-intersection.

3D Pose Estimation 3D Reconstruction

Deep Adaptive Proposal Network for Object Detection in Optical Remote Sensing Images

no code implementations19 Jul 2018 Lin Cheng, Xu Liu, Lingling Li, Licheng Jiao, Xu Tang

More recently, a two-stage detector Faster R-CNN is proposed and demonstrated to be a promising tool for object detection in optical remote sensing images, while the sparse and dense characteristic of objects in remote sensing images is complexity.

Object object-detection +2

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