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Posted: 26 Dec 2021 04:00

“Convolutional Neural Network” December 2021 — summary from PubMed and Zenodo

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“Convolutional Neural Network” December 2021 — summary from PubMed and Zenodo main image

The content below is machine-generated by Brevi Technologies’ NLG model, and the source content was collected from open-source databases/integrate APIs.

PubMed - summary generated by Brevi Assistant

Lately, in different industrial areas, including automated making processes, industrial robots are ending up being essential equipment; these robots perform repetitive tasks and boost the productivity of the production line with consistent precision and accuracy. Therefore, mistake diagnostics of industrial robots is an essential method to protect against the substantial economic losses that can be triggered by unexpected quit of an assembly line as a result of a commercial robot mistake. However, previous data-driven industrial robotic mistake diagnostics are limited because a pre-trained model constructed for a specific motion may not properly or regularly spot mistakes in other activities, due to motion disparities.

A magnetic resonance imaging series independent deep learning technique was established and verified to generate artificial computed tomography scans for MR led proton treatment. An unique MRI sequence independent sCT generator was developed, which recommends that the training phase of neural networks can be disengaged from specific MRI procurement methods.

Achieving high feature reproducibility while maintaining organic details is one of the main difficulties for the generalizability of existing radiomics studies. In the validation phase, the re-trained CNN was verified on an outside cohort of 223 lung cancer cells patients' CT photos gotten utilizing various CT scanners and kernels.

This research study recommends a convolutional neural network -based computer-aided medical diagnosis system for the quality category of human glioma by making use of mid-infrared spectroscopic mappings. Contrasted with the efficiency of the CNN-CAD system based upon the 1D vibrational spectroscopy, we discovered that the mean diagnostic accuracy of the recombined MIR spectroscopic mappings at tops of 2917 cm-1, 1539 cm-1 and 1234 cm-1 on the test set performed greater and the model had a lot more stable patterns.

Tree blossoms have been widely used in the avoidance and therapy of a range of diseases in standard Chinese medication for thousand years. The dataset offer a collection of blossom photos on conventional Chinese natural herbs assists Chinese pharmacologists to classify the categories of Chinese natural herbs.

Source texts:

Zenodo - summary generated by Brevi Assistant

Predictive maintenance is an effective strategy made use of to minimize price by minimizing the break down stoppages and production loss. The PdM model based on the CNN-LSTM method shows far better forecast accuracy contrasted to the regular LSTM, where the typical F-Score rises to 93.34% in the situation of routine LSTM to 97.48% for the recommended CNN-LSTM.

This research recommended automated ordered classification of scanned papers with quality content that have unstructured text and unique patterns using convolutional neural network and regular expression approach.

The research information using digital correspondence documents with layout PDF images from Pusat Data Teknologi dan Informasi.

Little unmanned airborne vehicles applications have appeared in many fields, including conservation management. The efficiency of the recommended Faster R-CNN with atrous convolutional filters in the foundation network was proven to be impressive in our circumstances by contrasting to various other detection designs.

The human brain easily fixes the complicated computational task of audio localization by making use of a mixture of spatial hints. This work leads the way for future research studies combining neural network models with empirical dimensions of neural task to decipher the complex computational mechanisms underlying neural noise location encoding in the human auditory pathway.

Object recognition and detection are well-studied problems with a created set of almost conventional services. The dataset contains five hundred video clips for fifty various identity document types.

This can serve as an example of how to use Brevi Assistant and integrated APIs to analyze text content.

Source texts:


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