The second experiment replicated this latter effect and indicated that mood enhancement is mediated by perceptions of similarity to the target; the more similar the threatened, low self-esteem persons thought they were to the target, the better they felt after the comparison. Implications for ...
Heller (2016) Self-similarity and Reynolds number invariance in Froude modelling - Presentation Beyond their inception region from wide-banded inlet noise, roll waves on an inclined plane increase their amplitude and separation downstream in a scale-i... V Heller 被引量: 7发表: 2016年 Self-simi...
We show that simple patch-based models, such as epitomes, can have superior performance to the current state of the art in semantic segmentation and label super-resolution, which uses deep convolutional neural networks. We derive a new training algorithm for epitomes which allows, for the first...
By considering the low rank constraint, our online metric learning model not only can provide competitive performance compared with the state-of-the-art methods, but also guarantees convergence. A bi-linear graph is also defined to model the pair-wise similarity, and an unseen sample is labeled...
Document Similarity Self-Join with MapReduce iven a collection of objects, the Similarity Self-Join problem requires to discover all those pairs of objects whose similarity is above a user defined thr... R Baraglia,GDF Morales,C Lucchese - IEEE International Conference on Data Mining 被引量: ...
To determine the level of similarity between actor perceptions of peer delinquency, actor self-reported delinquency, and partner self-reported delinquency, three series of confirmatory factor analyses (CFAs) are estimated. In this instance, the use of CFAs is a robust and quite useful method to ...
Self-similarity based super-resolution (SR) algorithms are able to produce visually pleasing results without extensive training on external databases. Such algorithms exploit the statistical prior that patches in a natural image tend to recur within and across scales of the same image. However, the ...
Our experiments on three real-world text datasets show that the proposed approach using binarised Laplacian Eigenmap (LapEig) and linear Support Vector Machine (SVM) outperforms state-of-the-art techniques significantly. 展开 关键词: laplacian eigenmap semantic hashing similarity search support vector...
August, 2022: BEiT-3 - a general-purpose multimodal foundation model, which achieves state-of-the-art transfer performance on both vision and vision-language tasks July, 2022: SimLM - Large-scale self-supervised pre-training for similarity matching June, 2022: DiT and LayoutLMv3 were accepted ...
We keep the convolutional feature maps as the image embedding to preserve spatial structures and adopt Earth Mover's Distance (EMD) to compute the similarity between two embeddings. Our Faster R-CNN (ResNet50-FPN) baseline achieves 39.8% mAP on COCO, which is on par with the state of the...