AIMC Topic: Algorithms

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A Novel Memory-Scheduling Strategy for Large Convolutional Neural Network on Memory-Limited Devices.

Computational intelligence and neuroscience
Recently, machine learning, especially deep learning, has been a core algorithm to be widely used in many fields such as natural language processing, speech recognition, object recognition, and so on. At the same time, another trend is that more and ...

Spectral and Temporal Feature Learning With Two-Stream Neural Networks for Mental Workload Assessment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
People's mental workload profoundly affects their work efficiency and health. Mental workload assessment can be used to effectively avoid serious accidents caused by excessive mental workload. Both electroencephalogram (EEG) spectral features and its...

Application of Deep Learning Algorithm in Cervical Cancer MRI Image Segmentation Based on Wireless Sensor.

Journal of medical systems
With the development of medical technology in China, new difficulties are gradually emerging in traditional medicine. Cervical cancer MRI image segmentation technology based on wireless network is one of the most famous means. But the traditional tec...

An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning.

Journal of medical systems
Approximately 300 million people are afflicted with asthma around the world, with the estimated death rate of 250,000 cases, indicating the significance of this disease. If not treated, it can turn into a serious public health problem. The best metho...

JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation.

IEEE transactions on bio-medical engineering
OBJECTIVE: The purpose of this paper is to propose a novel algorithm for joint optic disc and cup segmentation, which aids the glaucoma detection.

Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging.

IEEE transactions on medical imaging
Detecting acoustic shadows in ultrasound images is important in many clinical and engineering applications. Real-time feedback of acoustic shadows can guide sonographers to a standardized diagnostic viewing plane with minimal artifacts and can provid...

Coupling Molecular Dynamics and Deep Learning to Mine Protein Conformational Space.

Structure (London, England : 1993)
Flexibility is often a key determinant of protein function. To elucidate the link between their molecular structure and role in an organism, computational techniques such as molecular dynamics can be leveraged to characterize their conformational spa...

Multiclass Support Matrix Machines by Maximizing the Inter-Class Margin for Single Trial EEG Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Accurate classification of Electroencephalogram (EEG) signals plays an important role in diagnoses of different type of mental activities. One of the most important challenges, associated with classification of EEG signals is how to design an efficie...

Predicting Growth and Carcass Traits in Swine Using Microbiome Data and Machine Learning Algorithms.

Scientific reports
In this paper, we evaluated the power of microbiome measures taken at three time points over the growth test period (weaning, 15 and 22 weeks) to foretell growth and carcass traits in 1039 individuals of a line of crossbred pigs. We measured predicti...

Regression Algorithm of Bone Age Estimation of Knee-joint Based on Principal Component Analysis and Support Vector Machine.

Fa yi xue za zhi
Objective To establish a regression algorithm model that applies to bone age estimation of Xinjiang Uygur adolescents with machine learning methods such as histogram of oriented gradient (HOG), local binary patterns (LBP), support vector machine (SVM...