5.5.1 Cityscapes benchmark testing dataset We used the state-of-the-art method Xception71-DPC as the semantic branch, and trained the detail branch on the trainval fine set because the finely annotated images in this set can provide valid training data for segmentation details. Our proposed ...
Through extensive testing on both simulated and real datasets, we have demonstrated the remarkable performance of MAC-ErrorReads, particularly the NB model, which achieved high accuracy and precision in read classification. Applying MAC-ErrorReads to real sequencing data from E. coli, S. aureus, H...
We are instead resolving that problem by the explicit inversion testing already discussed. In the case of Merlin, however, the disadvantage in using the Viterbi algorithm is of a different nature, and lies in the construction of the state space, when used for genotype and haplotype inference. ...
This evaluation is conducted com- prehensively through testing with both simulated and real sequencing experiments across different organisms. Methods MAC-ErrorReads converts the process of filtering erroneous NGS reads into a machine learning classification problem. MAC-ErrorReads learns a mapping ...
For simulation, one lakh samples have been taken from 51 IoT nodes from a hydraulic test rig. In the data set, 80% of the data are considered training data, and 20% is taken as testing data. Here the selected nodes 1, 5, 11, 14, 18, 24, 39, and 48 are taken as neighbor ...
For simulation, one lakh samples have been taken from 51 IoT nodes from a hydraulic test rig. In the data set, 80% of the data are considered training data, and 20% is taken as testing data. Here the selected nodes 1, 5, 11, 14, 18, 24, 39, and 48 are taken as neighbor ...