Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions using expression similarity or RNA velocity to reconstruct state-change trajectories; however, trajectory inference does not incorporate valuable time point informat
Based on these findings, we used the Spearman correlation approach to showcase the linear changing molecules during human aging. The permutation test was also used to get the permutated P values for each feature. In brief, each feature was subjected to sample label shuffling followed by a ...
We propose a novel framework based on neural networks to identify the sentiment of opinion targets in a comment/review. Our framework adopts multiple-attention mechanism to capture sentiment features separated by a long distance, so that it is more robust against irrelevant information. The results ...
We have introduced the AI-driven autonomous workflow for accurate and rapid cell tomographic reconstruction. Accurate detection of the rotation angle is crucial for maintaining the fidelity of tomographic reconstructions49. Although the automatic tracking of cell orientation in microscopic images is highly ...
To effectively break through these performance degradation issues, a multi-scale tire sidewall text region detection algorithm based on YOLOv5 is introduced, called YOLOT, which fuses comprehensive feature information in both width and depth directions. In this study, we firstly propose the Width and...
[227]introduced a promising feature descriptor, referred to as median robust LBP-TOP (MRLBP-TOP), that can learn patterns at different scales from image sequences.Dirichlet processFV (DPFV) has also been proposed to learn the global patterns from the segment-level features. In addition, ...
Motr: End-to-end multiple- 9542 object tracking with transformer. In Proceedings of the Eu- ropean Conference on Computer Vision. Springer, 2022. 2 [87] Wenwei Zhang, Hui Zhou, Shuyang Sun, Zhe Wang, Jian- ping Shi, and Chen Change Loy. Robust multi-modality multi-obj...
Figure 3a shows that feature-level fusion methods extract and combine features from input modality signals to create an informative representation for decision-making. These methods integrate features from different modalities to generate a robust multi-modal representation, which has been extensively studie...
In addition, a validation of the identified suitable sites could lead to a more robust and real interpretation of the results, either through aerial photography (drone) or a field visit to these sites. Future studies could consider extending the proposed method to investigate the theoretical energy...
Advances in computational capabilities combined with robust and optimized high-fidelity analysis tools has resulted in a trend to incorporate such methods already from the preliminary stage. In order to bridge the gap between capabilities and computational cost between high and low-fidelity methods, two...