parallel evolution Parallel forces parallel import parallel importing parallel interface Parallel Lives Parallel motion Parallel of altitude Parallel of declination parallel of latitude parallel operation parallel port parallel processing parallel resonance ...
A better explanation of the developed tool and its use implications. A new processing example using hyperspectral data in addition to Google Maps. A more detailed evaluation of the system using data sets with ground truth. A better presentation of processing results and achieved speedups on GPUs....
The TensorFlow that is used in the environment uses Single Instruction Multiple Instruction (SIMD), which is a type of parallel processing used to improve performance. The TensorFlow that you set up in the environment is designed to use oneAPI Deep Neural Network Library (oneDNN)....
text mining [2], bioinformatics [3,4], and activity recognition [5]. Learning accurate models requires generation of informative features. In many datasets, this process is labour intensive and requires significant domain
We presented parallel algorithms for building decision-tree classifiers on SMP systems. The proposed algorithms span the gamut of data and task parallelism. The MWK algorithm uses data parallelism from multiple attributes, but also uses task pipelining to overlap different computing phases within a tree...
integrating the principle of machine learning methodology with compression and information-processing methods. The results depict minimization in data loss along with a delay. The proposed work is 4.7 times better than theexisting methods. It did not concentrate on the energy factor andheterogeneous ...
Usereadallwith"UseParallel"option set totrueto enable parallel processing of the transform functions, in case you haveParallel Computing Toolbox™ license. Sincereadallfunction, by default, concatenates the output of thereadfunction over the first dimension, return the frames in a cell array and ...
The multi-modal feature fusion (MFF) module fuses the features extracted by SFE and TFE in parallel into MSTF to obtain more comprehensive feature information. A Light ResNet is designed based on the idea of residuals and depth-separable convolution. Compared to the traditional ResNet18, its ...
Mdlaccurately classifies approximately 92% of the observations in the test set. Extended Capabilities C/C++ Code Generation Generate C and C++ code using MATLAB® Coder™. GPU Arrays Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™. (since R20...
The proposed PLSTM method could be used for parallel sequence classification purposes. The PLSTM approach is evaluated on an automatic telecast genre sequences classification task and compared with different state-of-the-art architectures. Results show that the proposed PLSTM method outperforms the ...