For this benchmarking activity, we ran BERT, SSD, and ResNet-50 from the NVIDIA Deep Learning Examplesrepository. We ran the training and inference piece for 3 benchmarks on the NC-series machines mentioned above. BERT Bidirectional Encoder Representations from...
The high level features that were calculated from the tested models managed to classify the different land cover classes with significantly high accuracy rates i.e., above 99.9%. The experimental results demonstrate the great potentials of advanced deep-learning frameworks for the supervised ...
This section is responsible for generating and labelling the training data used to train the Machine Learning models. It has several options to change the generation algorithm and vary hyperparameters to that algorithm, as well as specifying number of dimensions and size of the maps. They are sav...
classes of serious segmentation errors altogether. This paper introduces a vectorial score that is sensitive to, and identifies, the most important classes of segmentation errors (over-, under-, and mis-segmentation) and what page components (lines, blocks, etc.) are affected. Unlike previous ...
dice_cetype_branch_loss:dice_ceaux_branch_loss:mse_ssimruntime_args:resume_training:Falsenum_epochs:2num_gpus:1batch_size:4num_workers:8#number workers for data loadermodel_input_size:256#size of the model inputdb_type:hdf5#One of (hdf5, zarr).wandb:True#Wandb loggingmetrics_to_cpu:...
Their applicability has been investigated in [60], to compensate for the lack of publicly available large-scale test databases, and in [18], to provide a taxonomy and further discussion. Several synthetic databases for training have been synthesized using generative frameworks relying on GANs. The...
Training of the quantum circuit is achieved by successive updates of the parametersθ, corresponding to specifications of single qubit operations and entangling gates. In this work, we use arbitrary single qubit rotations for the odd layers, and Mølmer-SørensenXXgates for the even layers. At...
Number of Classes N Number of Samples R2 Coefficient of Determination T Tree Pruning Item 1. Introduction Building energy benchmarking is a critical approach for building owners, managers, and policymakers, providing the seasonality of energy usage to stimulate informed decisions. By regularly tracking...
The data for each task is stored as abedfile. This file includes the genomic coordinates for each sample, as well as its split membership and potentially a label. Together with a reference genome, the file is used to extract the DNA sequences for training. Labels that are too complex to ...
pre-training in standard SSL settings such as linear and fine-tuning evaluations, as well as in low-label regimes. Moreover, we propose a set of domain-specific techniques that we experimentally show leads to a performance boost. Lastly, for the first time, we apply SSL to the challenging ...