AIMC Topic: Algorithms

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Applying Hybrid Lstm-Gru Model Based on Heterogeneous Data Sources for Traffic Speed Prediction in Urban Areas.

Sensors (Basel, Switzerland)
With the advent of the Internet of Things (IoT), it has become possible to have a variety of data sets generated through numerous types of sensors deployed across large urban areas, thus empowering the notion of smart cities. In smart cities, various...

MR-FPN: Multi-Level Residual Feature Pyramid Text Detection Network Based on Self-Attention Environment.

Sensors (Basel, Switzerland)
With humanity entering the age of intelligence, text detection technology has been gradually applied in the industry. However, text detection in a complex background is still a challenging problem for researchers to overcome. Most of the current algo...

Evaluation Algorithm for the Effectiveness of Stroke Rehabilitation Treatment Using Cross-Modal Deep Learning.

Computational and mathematical methods in medicine
It is important to study the evaluation algorithm for the stroke rehabilitation treatment effect to make accurate evaluation and optimize the stroke disease treatment plan according to the evaluation results. To address the problems of poor restorati...

Research on the Effectiveness of Probabilistic Stochastic Convolution Neural Network Algorithm in Physical Education Teaching Evaluation.

Computational intelligence and neuroscience
In practice, PE teaching evaluation based on probabilistic convolutional neural network still faces some practical problems. At present, the existing research mainly focuses on how to improve the accuracy of PE (physical education) teaching evaluatio...

Index Evaluation of Different Hospital Management Modes Based on Deep Learning Model.

Computational intelligence and neuroscience
In order to effectively improve the efficiency of hospital public management, we designed a hospital management index system based on deep learning model and analysed the application effect of reverse broadcast neural network model in hospital. The r...

Research on Multicamera Photography Image Art in BERT Motion Based on Deep Learning Mode.

Computational intelligence and neuroscience
In order to improve the artistic expression effect of photographic images, this article combines the deep learning model to conduct multicamera photographic image art research in BERT motion. Moreover, this article analyzes the external parameter err...

Transferability of features for neural networks links to adversarial attacks and defences.

PloS one
The reason for the existence of adversarial samples is still barely understood. Here, we explore the transferability of learned features to Out-of-Distribution (OoD) classes. We do this by assessing neural networks' capability to encode the existing ...

Performing protein fold recognition by exploiting a stack convolutional neural network with the attention mechanism.

Analytical biochemistry
Protein fold recognition is a critical step in protein structure and function prediction, and aims to ascertain the most likely fold type of the query protein. As a typical pattern recognition problem, designing a powerful feature extractor and metri...

Federated Learning in Medical Imaging: Part I: Toward Multicentral Health Care Ecosystems.

Journal of the American College of Radiology : JACR
With recent developments in medical imaging facilities, extensive medical imaging data are produced every day. This increasing amount of data provides an opportunity for researchers to develop data-driven methods and deliver better health care. Howev...

Research on Vehicle Lane Change Warning Method Based on Deep Learning Image Processing.

Sensors (Basel, Switzerland)
In order to improve vehicle driving safety in a low-cost manner, we used a monocular camera to study a lane-changing warning algorithm for highway vehicles based on deep learning image processing technology. We improved the mask region-based convolut...