AIMC Topic: Neural Networks, Computer

Clear Filters Showing 13591 to 13600 of 31376 articles

Pedestrian and Animal Recognition Using Doppler Radar Signature and Deep Learning.

Sensors (Basel, Switzerland)
Pedestrian occurrences in images and videos must be accurately recognized in a number of applications that may improve the quality of human life. Radar can be used to identify pedestrians. When distinct portions of an object move in front of a radar,...

Experimental analysis and parameter optimization on the reduction of NOx from diesel engine using RSM and ANN Model.

Environmental science and pollution research international
The major emission sources of NO are from automobiles, trucks, and various non-road vehicles, power plants, coal fired boilers, cement kilns, turbines, etc. Plasma reactor technology is widely used in gas conversion applications, such as NOx conversi...

Deep learning-based plane pose regression in obstetric ultrasound.

International journal of computer assisted radiology and surgery
PURPOSE: In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimensional (2D) US image represents a major challenge in skill acquisition. We aim to build a US plane local...

Electrocardiogram Biometrics Using Transformer's Self-Attention Mechanism for Sequence Pair Feature Extractor and Flexible Enrollment Scope Identification.

Sensors (Basel, Switzerland)
The existing electrocardiogram (ECG) biometrics do not perform well when ECG changes after the enrollment phase because the feature extraction is not able to relate ECG collected during enrollment and ECG collected during classification. In this rese...

A Universal Detection Method for Adversarial Examples and Fake Images.

Sensors (Basel, Switzerland)
Deep-learning technologies have shown impressive performance on many tasks in recent years. However, there are multiple serious security risks when using deep-learning technologies. For examples, state-of-the-art deep-learning technologies are vulner...

Multiscale and Hierarchical Feature-Aggregation Network for Segmenting Medical Images.

Sensors (Basel, Switzerland)
We propose an encoder-decoder architecture using wide and deep convolutional layers combined with different aggregation modules for the segmentation of medical images. Initially, we obtain a rich representation of features that span from low to high ...

A Novel Transformer-Based Attention Network for Image Dehazing.

Sensors (Basel, Switzerland)
Image dehazing is challenging due to the problem of ill-posed parameter estimation. Numerous prior-based and learning-based methods have achieved great success. However, most learning-based methods use the changes and connections between scale and de...

Identifying Blood Biomarkers for Dementia Using Machine Learning Methods in the Framingham Heart Study.

Cells
Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for ...

Deep parameter-free attention hashing for image retrieval.

Scientific reports
Deep hashing method is widely applied in the field of image retrieval because of its advantages of low storage consumption and fast retrieval speed. There is a defect of insufficiency feature extraction when existing deep hashing method uses the conv...

Emotion Analysis Model of Microblog Comment Text Based on CNN-BiLSTM.

Computational intelligence and neuroscience
Aiming at the problems of over reliance on labor and low generalization of traditional emotion analysis methods based on dictionary and machine learning, an emotion analysis model of microblog comment text based on deep learning is proposed. Firstly,...