AIMC Topic: Neural Networks, Computer

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A Deep Learning Model Incorporating Knowledge Representation Vectors and Its Application in Diabetes Prediction.

Disease markers
The deep learning methods for various disease prediction tasks have become very effective and even surpass human experts. However, the lack of interpretability and medical expertise limits its clinical application. This paper combines knowledge repre...

Skill Movement Trajectory Recognition of Freestyle Skiing U-Shaped Field Based on Deep Learning and Multitarget Tracking Algorithm.

Computational intelligence and neuroscience
Freestyle skiing U-shaped field is a snow sport that uses double boards to perform a series of action skills in a U-shaped pool, which requires very high skills for athletes. In this era of deep learning, in order to develop a more scientific trainin...

SFN: A Novel Scalable Feature Network for Vulnerability Representation of Open-Source Codes.

Computational intelligence and neuroscience
Vulnerability detection technology has become a hotspot in the field of software security, and most of the current methods do not have a complete consideration during code characterizing, which leads to problems such as information loss. Therefore, t...

Sparrow Search Algorithm-Optimized Long Short-Term Memory Model for Stock Trend Prediction.

Computational intelligence and neuroscience
The long short-term memory (LSTM) network is especially suitable for dealing with time series-related problems, which has led to a wide range of applications in analyzing stock market quotations and predicting future price trends. However, the select...

Segmentation of Medical Image Using Novel Dilated Ghost Deep Learning Model.

Computational intelligence and neuroscience
Image segmentation and computer vision are becoming more important in computer-aided design. A computer algorithm extracts image borders, colours, and textures. It also depletes resources. Technical knowledge is required to extract information about ...

A deep learning-based method for classification, detection, and localization of weeds in turfgrass.

Pest management science
BACKGROUND: Precision spraying of synthetic herbicides can reduce herbicide input. Previous research demonstrated the effectiveness of using image classification neural networks for detecting weeds growing in turfgrass, but did not attempt to discrim...

Multi-label classification of fundus images with graph convolutional network and LightGBM.

Computers in biology and medicine
Early detection and treatment of retinal disorders are critical for avoiding irreversible visual impairment. Given that patients in the clinical setting may have various types of retinal illness, the development of multi-label fundus disease detectio...

Linear or non-linear multivariate calibration models? That is the question.

Analytica chimica acta
Concepts from data science, machine learning, deep learning and artificial neural networks are spreading in many disciplines. The general idea is to exploit the power of statistical tools to interpret complex and, in many cases, non-linear data. Spec...

Masked Joint Bilateral Filtering via Deep Image Prior for Digital X-Ray Image Denoising.

IEEE journal of biomedical and health informatics
Medical image denoising faces great challenges. Although deep learning methods have shown great potential, their efficiency is severely affected by millions of trainable parameters. The non-linearity of neural networks also makes them difficult to be...

Deep Features Aggregation-Based Joint Segmentation of Cytoplasm and Nuclei in White Blood Cells.

IEEE journal of biomedical and health informatics
White blood cells (WBCs), also known as leukocytes, are one of the valuable parts of the blood and immune system. Typically, pathologists use microscope for the manual inspection of blood smears which is a time-consuming, error-prone, and labor-inten...