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Works174 from public data
- Review of Visual Saliency Detection With Comprehensive Information419
Different types of saliency detection algorithms are reviewed, the important issues of the existing methods are summarized, the existent problems and future works are discussed, and the experimental analysis and discussion are conducted to provide a holistic overview of differentSaliency detection methods.
- Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion235
A measure to evaluate the reliability of depth map, and use it to reduce the influence of poor depth map on saliency detection, and two saliency maps are integrated into a final saliency map through weighted-sum method according to their importance.
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- An Iterative Co-Saliency Framework for RGBD Images123
An iterative RGBD co-saliency framework is proposed, which utilizes the existing single saliency maps as the initialization, and generates the final RGBD Co-Saliency map by using a refinement-cycle model.
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- HSCS: Hierarchical Sparsity Based Co-saliency Detection for RGBD Images104
A novel co-saliency detection method for RGBD images based on hierarchical sparsity reconstruction and energy function refinement is proposed, which outperforms the state-of-the-art algorithms both qualitatively and quantitatively.
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- Fast reference frame selection based on content similarity for low complexity HEVC encoder93
A fast reference frame selection algorithm for the HEVC encoder that efficiently removes the encoding complexity of the best reference frame decision process and the rate distortion performance degradation is negligible.
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- Transferred deep learning based waveform recognition for cognitive passive radar81
A novel transferred deep learning waveform recognition method which makes use of multi-scale convolution and temporal dependency characteristics to improve the recognition performance and significantly outperforms the state-of-the-art methods.
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- Joint spatial-spectral hyperspectral image classification based on convolutional neural network72
Experimental results on two datasets demonstrate that the proposed joint spatial-spectral hyperspectral image classification method outperforms other state-of-the-art methods qualitatively and quantitatively.
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- Adaptive Fractional-Pixel Motion Estimation Skipped Algorithm for Efficient HEVC Motion Estimation69
An adaptive fractional-pixel ME skipped scheme is proposed for low-complexity HEVC ME, which reduces ME encoding time by an average of 63.22% while encoding efficiency performance is maintained.
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- Semi-Heterogeneous Three-Way Joint Embedding Network for Sketch-Based Image Retrieval61
A novel semi-heterogeneous three-way joint embedding network (Semi3-Net) is proposed, which integrates three branches (a sketch branch, a natural image branch, and an edgemap branch) to learn more discriminative cross-domain feature representations for the SBIR task.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-16. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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