CNN特征可视化相关论文

Learning Deep Features for Discriminative Localization

https://arxiv.org/pdf/1512.04150.pdf

Top-down Neural Attention by Excitation Backprop

https://arxiv.org/pdf/1608.00507.pdf

Grad-CAM:Visual Explanations from Deep Networks via Gradient-based Localization

https://arxiv.org/pdf/1610.02391.pdf https://github.com/ramprs/grad-cam

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

https://arxiv.org/pdf/1710.11063.pdf

Tell Me Where to Look: Guided Attention Inference Network

https://arxiv.org/pdf/1802.10171.pdf

CNN Fixations: An unraveling approach to visualize the discriminative image regions

https://arxiv.org/pdf/1708.06670.pdf

LEARNING HOW TO EXPLAIN NEURAL NETWORKS: PATTERNNET AND PATTERNATTRIBUTION

https://arxiv.org/pdf/1705.05598.pdf

Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach

https://arxiv.org/pdf/1703.08448.pdf

Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers

https://arxiv.org/pdf/1604.00825.pdf

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0130140\&type=printable

Mining Objects: Fully Unsupervised Object Discovery and Localization From a Single Image

https://arxiv.org/pdf/1902.09968.pdf

weakly supervised object detections

C-WSL: Count-guided Weakly Supervised Localization

https://arxiv.org/pdf/1711.05282.pdf

Improved Techniques for the Weakly-Supervised Object Localization

https://arxiv.org/pdf/1802.07888.pdf

ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks

https://arxiv.org/pdf/1511.03776.pdf

Weakly Supervised Region Proposal Network and Object Detection http://openaccess.thecvf.com/content_ECCV_2018/papers/Peng_Tang_Weakly_Supervised_Region_ECCV_2018_paper.pdf

Saliency Guided End-to-End Learning for Weakly Supervised Object Detection

https://www.ijcai.org/proceedings/2017/0285.pdf

Collaborative Learning for Weakly Supervised Object Detection

https://www.ijcai.org/proceedings/2018/0135.pdf

Training object class detectors with click supervision

http://calvin.inf.ed.ac.uk/wp-content/uploads/Publications/papadopoulos17cvpr.pdf

Seed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation

https://arxiv.org/pdf/1603.06098.pdf

Weakly Supervised Instance Segmentation using Class Peak Response

https://arxiv.org/pdf/1804.00880.pdf

博士,担任《Mechanical System and Signal Processing》审稿专家,担任
《中国电机工程学报》优秀审稿专家,《控制与决策》,《系统工程与电子技术》等EI期刊审稿专家,担任《计算机科学》,《电子器件》 , 《现代制造过程》 ,《船舶工程》 ,《轴承》 ,《工矿自动化》 ,《重庆理工大学学报》 ,《噪声与振动控制》 ,《机械传动》 ,《机械强度》 ,《机械科学与技术》 ,《机床与液压》,《声学技术》,《应用声学》,《石油机械》,《西安工业大学学报》等中文核心审稿专家。
擅长领域:现代信号处理,机器学习,深度学习,数字孪生,时间序列分析,设备缺陷检测、设备异常检测、设备智能故障诊断与健康管理PHM等。

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