AIMC Topic: Neural Networks, Computer

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Application of Improved LSTM Algorithm in Macroeconomic Forecasting.

Computational intelligence and neuroscience
From a macro perspective, futures index of agricultural products can reflect the trend of macroeconomy and can also have an early warning effect on the possible crisis and provide a reference for the government's economic forecast and macro control. ...

3D hemisphere-based convolutional neural network for whole-brain MRI segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Whole-brain segmentation is a crucial pre-processing step for many neuroimaging analyses pipelines. Accurate and efficient whole-brain segmentations are important for many neuroimage analysis tasks to provide clinically relevant information. Several ...

A CSI-Based Human Activity Recognition Using Deep Learning.

Sensors (Basel, Switzerland)
The Internet of Things (IoT) has become quite popular due to advancements in Information and Communications technologies and has revolutionized the entire research area in Human Activity Recognition (HAR). For the HAR task, vision-based and sensor-ba...

Neural Network-Oriented Big Data Model for Yoga Movement Recognition.

Computational intelligence and neuroscience
The use of computer vision for target detection and recognition has been an interesting and challenging area of research for the past three decades. Professional athletes and sports enthusiasts in general can be trained with appropriate systems for c...

Enhanced precision of real-time control photothermal therapy using cost-effective infrared sensor array and artificial neural network.

Computers in biology and medicine
Photothermal therapy (PTT) requires tight thermal dose control to achieve tumor ablation with minimal thermal injury on surrounding healthy tissues. In this study, we proposed a real-time closed-loop system for monitoring and controlling the temperat...

A deep learning model for burn depth classification using ultrasound imaging.

Journal of the mechanical behavior of biomedical materials
Identification of burn depth with sufficient accuracy is a challenging problem. This paper presents a deep convolutional neural network to classify burn depth based on altered tissue morphology of burned skin manifested as texture patterns in the ult...

FCL-Net: Towards accurate edge detection via Fine-scale Corrective Learning.

Neural networks : the official journal of the International Neural Network Society
Integrating multi-scale predictions has become a mainstream paradigm in edge detection. However, most existing methods mainly focus on effective feature extraction and multi-scale feature fusion while ignoring the low learning capacity in fine-level ...

Sparsity-control ternary weight networks.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks (DNNs) have been widely and successfully applied to various applications, but they require large amounts of memory and computational power. This severely restricts their deployment on resource-limited devices. To address this iss...

Self-paced learning and privileged information based KRR classification algorithm for diagnosis of Parkinson's disease.

Neuroscience letters
Computer aided diagnosis (CAD) methods for Parkinson's disease (PD) can assist clinicians in diagnosis and treatment. Magnetic resonance imaging (MRI) based CAD methods can help reveal structural changes in brain. Classifier is a key component in CAD...

Kohonen Network-Based Adaptation of Non Sequential Data for Use in Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Convolutional neural networks have become one of the most powerful computing tools of artificial intelligence in recent years. They are especially suitable for the analysis of images and other data that have an inherent sequence structure, such as ti...