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Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach
We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems. ClassificationExpand
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HCP: A Flexible CNN Framework for Multi-Label Image Classification
  • Yunchao Wei, Wei Xia, +5 authors S. Yan
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 September 2016
Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still remains an openExpand
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Cross-Modal Retrieval With CNN Visual Features: A New Baseline
Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrievalExpand
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Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks
Question generation, the task of automatically creating questions that can be answered by a certain span of text within a given passage, is important for question-answering and conversational systemsExpand
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CNN: Single-label to Multi-label
Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still remains an openExpand
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Depth Map Driven Hole Filling Algorithm Exploiting Temporal Correlation Information
The depth-image-based-rendering is a key technique to realize free viewpoint television. However, one critical problem in these systems is filling the disocclusion due to the 3-D warping process.Expand
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Contrast Enhancement-Based Forensics in Digital Images
As a retouching manipulation, contrast enhancement is typically used to adjust the global brightness and contrast of digital images. Malicious users may also perform contrast enhancement locally forExpand
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BotGraph: Large Scale Spamming Botnet Detection
Network security applications often require analyzing huge volumes of data to identify abnormal patterns or activities. The emergence of cloud-computing models opens up new opportunities to addressExpand
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Pairwise Prediction-Error Expansion for Efficient Reversible Data Hiding
In prediction-error expansion (PEE) based reversible data hiding, better exploiting image redundancy usually leads to a superior performance. However, the correlations among prediction-errors are notExpand
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Where the Sidewalk Ends: Extending the Internet AS Graph Using Traceroutes from P2P Users
An accurate Internet topology graph is important in many areas of networking, from understanding ISP business relationships to diagnosing network anomalies. Most Internet mapping efforts have derivedExpand
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