AIMC Topic: Neural Networks, Computer

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Object detectors involving a NAS-gate convolutional module and capsule attention module.

Scientific reports
Several state-of-the-art object detectors have demonstrated outstanding performances by optimizing feature representation through modification of the backbone architecture and exploitation of a feature pyramid. To determine the effectiveness of this ...

Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany.

Scientific reports
During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and interpretable forecasts of disease incidents are a vital tool for policymakers to manage healthcare resou...

Network analytics and machine learning for predicting length of stay in elderly patients with chronic diseases at point of admission.

BMC medical informatics and decision making
BACKGROUND: An aging population with a burden of chronic diseases puts increasing pressure on health care systems. Early prediction of the hospital length of stay (LOS) can be useful in optimizing the allocation of medical resources, and improving he...

New Progress in Artificial Intelligence Algorithm Research Based on Big Data Processing of IOT Systems on Intelligent Production Lines.

Computational intelligence and neuroscience
Intelligent production line is the abbreviation of intelligent production line. Intelligent production line refers to a form of production organization that uses intelligent manufacturing technology to realize the production process of products. The ...

Analysis of Bank Credit Risk Evaluation Model Based on BP Neural Network.

Computational intelligence and neuroscience
Commercial banks are of great value to social and economic development. Therefore, how to accurately evaluate their credit risk and establish a credit risk prevention system has important theoretical and practical significance. This paper combines BP...

Short-Text Classification Detector: A Bert-Based Mental Approach.

Computational intelligence and neuroscience
With the continuous development of the Internet, social media based on short text has become popular. However, the sparsity and shortness of essays will restrict the accuracy of text classification. Therefore, based on the Bert model, we capture the ...

Deep Neural Networks for Medical Image Segmentation.

Journal of healthcare engineering
Image segmentation is a branch of digital image processing which has numerous applications in the field of analysis of images, augmented reality, machine vision, and many more. The field of medical image analysis is growing and the segmentation of th...

Artificial intelligence software available for medical devices: surgical phase recognition in laparoscopic cholecystectomy.

Surgical endoscopy
BACKGROUND: Surgical process modeling automatically identifies surgical phases, and further improvement in recognition accuracy is expected with deep learning. Surgical tool or time series information has been used to improve the recognition accuracy...

Lightweight Deep Neural Network for Articulated Joint Detection of Surgical Instrument in Minimally Invasive Surgical Robot.

Journal of digital imaging
Vision-based detection and tracking of surgical instrument are attractive because it relies purely on surgical instrument already in the operating scenario. The vision knowledge of the surgical instruments is a crucial piece of topic for surgical tas...

TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classification.

Neural networks : the official journal of the International Neural Network Society
Nuclei segmentation and classification of hematoxylin and eosin-stained histology images is a challenging task due to a variety of issues, such as color inconsistency that results from the non-uniform manual staining operations, clustering of nuclei,...