AIMC Topic: Deep Learning

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Development of Smartphone Application for Markerless Three-Dimensional Motion Capture Based on Deep Learning Model.

Sensors (Basel, Switzerland)
To quantitatively assess pathological gait, we developed a novel smartphone application for full-body human motion tracking in real time from markerless video-based images using a smartphone monocular camera and deep learning. As training data for de...

Systematic prediction of degrons and E3 ubiquitin ligase binding via deep learning.

BMC biology
BACKGROUND: Degrons are short linear motifs, bound by E3 ubiquitin ligase to target protein substrates to be degraded by the ubiquitin-proteasome system. Mutations leading to deregulation of degron functionality disrupt control of protein abundance d...

Multimodal image translation via deep learning inference model trained in video domain.

BMC medical imaging
BACKGROUND: Current medical image translation is implemented in the image domain. Considering the medical image acquisition is essentially a temporally continuous process, we attempt to develop a novel image translation framework via deep learning tr...

Human Gait Analysis: A Sequential Framework of Lightweight Deep Learning and Improved Moth-Flame Optimization Algorithm.

Computational intelligence and neuroscience
Human gait recognition has emerged as a branch of biometric identification in the last decade, focusing on individuals based on several characteristics such as movement, time, and clothing. It is also great for video surveillance applications. The ma...

Biomechanics of Volleyball Players' Run-Up and Take-Off Link under Deep Learning.

Computational intelligence and neuroscience
In volleyball, the correct approach and start (including the number of steps and stride speed) are a prerequisite for all technical movements to attack. It can not only improve the horizontal speed of the athlete, but also properly convert the total ...

Research on Intelligent Video Detection of Small Targets Based on Deep Learning Intelligent Algorithm.

Computational intelligence and neuroscience
Compared with the traditional object detection algorithm, the object detection algorithm based on deep learning has stronger robustness to complex scenarios, which is the hot direction of current research. According to the process characteristics of ...

Detection of WBC, RBC, and Platelets in Blood Samples Using Deep Learning.

BioMed research international
A blood count is one of the most important diagnostic tools in medicine and one of the most common procedures. It can reveal important changes in the body and is commonly used as the first stage in the process of evaluating patients' health. Even tho...

COVID-19 Classification from Chest X-Ray Images: A Framework of Deep Explainable Artificial Intelligence.

Computational intelligence and neuroscience
COVID-19 detection and classification using chest X-ray images is a current hot research topic based on the important application known as medical image analysis. To halt the spread of COVID-19, it is critical to identify the infection as soon as pos...

Unsupervised deep learning supports reclassification of Bronze age cypriot writing system.

PloS one
Ancient undeciphered scripts present problems of different nature, not just tied to linguistic identification. The undeciphered Cypro-Minoan script from second millennium BCE Cyprus, for instance, currently does not have a standardized, definitive in...

Feature-level ensemble approach for COVID-19 detection using chest X-ray images.

PloS one
Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), also known as the coronavirus disease 2019 (COVID-19), has threatened many human beings around the world and capsized economies at unprecedented magnitudes. Therefore, the detection of thi...