AIMC Topic: Deep Learning

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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...

Sports Deep Learning Method Based on Cognitive Human Behavior Recognition.

Computational intelligence and neuroscience
An in-depth learning-based approach is designed to develop the ability to recognize human behavior on the move. We introduce 3D residual structures and create 3D residual models. In order to get the most out of the data relationship of several consec...

Arm Movement Analysis Technology of Wushu Competition Image Based on Deep Learning.

Computational intelligence and neuroscience
In order to improve the recognition accuracy of action poses for athletes in martial arts competitions, it is considered that a single frame pose does not have the temporal features required for sequential actions. Based on deep learning, this paper ...

Analysis of College Students' Network Moral Behavior by the History of Ideological and Political Education under Deep Learning.

Computational intelligence and neuroscience
The research on the history of ideological and political education (IPE) is the basis for deepening it, and it is also of great help to higher education. The diversity of network information also easily leads to poor guidance for college students who...

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 algorithm for classification of oral lichen planus lesions from photographic images: A retrospective study.

Journal of stomatology, oral and maxillofacial surgery
INTRODUCTION: Deep learning methods have recently been applied for the processing of medical images, and they have shown promise in a variety of applications. This study aimed to develop a deep learning approach for identifying oral lichen planus les...

DEEP LEARNING ALGORITHMS SHOW SOME POTENTIAL AS AN ADJUNCTIVE TOOL IN CARIES DIAGNOSIS.

The journal of evidence-based dental practice
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Mohammad-Rahimi H, Reza Motamedian S, Hossein Rohban M, Krois J, Uribe SE, Mahmoudinia E, Rokhshad R, Nadimi M, Schwendicke F, Deep learning for caries detection: A systematic review, J Dent, 2022,122, 104...

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...

Deep learning-based medical image segmentation of the aorta using XR-MSF-U-Net.

Computer methods and programs in biomedicine
PURPOSE: This paper proposes a CT images and MRI segmentation technology of cardiac aorta based on XR-MSF-U-Net model. The purpose of this method is to better analyze the patient's condition, reduce the misdiagnosis and mortality rate of cardiovascul...

Predicting Patient Demographics From Chest Radiographs With Deep Learning.

Journal of the American College of Radiology : JACR
BACKGROUND: Deep learning models are increasingly informing medical decision making, for instance, in the detection of acute intracranial hemorrhage and pulmonary embolism. However, many models are trained on medical image databases that poorly repre...