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06/03/2023
Message-passing selection: Towards interpretable GNNs for graph classification
In this paper, we strive to develop an interpretable GNNs' inference par...
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05/10/2023
Multi-Prompt with Depth Partitioned Cross-Modal Learning
In recent years, soft prompt learning methods have been proposed to fine...
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08/02/2022
Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization
Image cartoonization is recently dominated by generative adversarial net...
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06/26/2022
Multi-view Feature Augmentation with Adaptive Class Activation Mapping
We propose an end-to-end-trainable feature augmentation module built for...
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09/13/2021
CarNet: A Lightweight and Efficient Encoder-Decoder Architecture for High-quality Road Crack Detection
Pixel-wise crack detection is a challenging task because of poor continu...
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07/24/2021
Inferring Economic Condition Uncertainty from Electricity Big Data
Inferring the uncertainties in economic conditions are of significant im...
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06/29/2021
Fast and Accurate Road Crack Detection Based on Adaptive Cost-Sensitive Loss Function
Numerous detection problems in computer vision, including road crack det...
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05/22/2021
Two-stage Training for Learning from Label Proportions
Learning from label proportions (LLP) aims at learning an instance-level...
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11/05/2019
Joint Ranking SVM and Binary Relevance with Robust Low-Rank Learning for Multi-Label Classification
Multi-label classification studies the task where each example belongs t...
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09/05/2019
Learning from Label Proportions with Generative Adversarial Networks
In this paper, we leverage generative adversarial networks (GANs) to der...
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12/12/2016
PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning
Positive instance detection, especially for these in positive bags (true...
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10/21/2016
