AIMC Topic: Data Collection

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Automated Cognitive Health Assessment Using Partially Complete Time Series Sensor Data.

Methods of information in medicine
BACKGROUND: Behavior and health are inextricably linked. As a result, continuous wearable sensor data offer the potential to predict clinical measures. However, interruptions in the data collection occur, which create a need for strategic data imputa...

A Residual-Inception U-Net (RIU-Net) Approach and Comparisons with U-Shaped CNN and Transformer Models for Building Segmentation from High-Resolution Satellite Images.

Sensors (Basel, Switzerland)
Building segmentation is crucial for applications extending from map production to urban planning. Nowadays, it is still a challenge due to CNNs' inability to model global context and Transformers' high memory need. In this study, 10 CNN and Transfor...

Bridge crack detection based on improved single shot multi-box detector.

PloS one
Owing to the development of computerized vision technology, object detection based on convolutional neural networks is being widely used in the field of bridge crack detection. However, these networks have limited utility in bridge crack detection be...

Research on the Predictive Analysis of Park Landscape Design and Cost Based on RNN Model.

Computational intelligence and neuroscience
As people's awareness of the environment gradually increases and their requirements for the comfort of living space become higher, landscape design has also ushered in a golden period of development. With the increasing investment in landscape constr...

ConcentrateNet: Multi-Scale Object Detection Model for Advanced Driving Assistance System Using Real-Time Distant Region Locating Technique.

Sensors (Basel, Switzerland)
This paper proposes a deep learning based object detection method to locate a distant region in an image in real-time. It concentrates on distant objects from a vehicular front camcorder perspective, trying to solve one of the common problems in Adva...

Rotating Single-Antenna Spoofing Signal Detection Method Based on IPNN.

Sensors (Basel, Switzerland)
The traditional carrier-phase differential detection technology mainly relies on the spatial processing method, which uses antenna arrays or moving antennas to detect spoofing signals, but it cannot be applied to static single-antenna receivers. Aimi...

Intelligent Detection of Hazardous Goods Vehicles and Determination of Risk Grade Based on Deep Learning.

Sensors (Basel, Switzerland)
Currently, deep learning has been widely applied in the field of object detection, and some relevant scholars have applied it to vehicle detection. In this paper, the deep learning EfficientDet model is analyzed, and the advantages of the model in th...

Improving the Accuracy of an R-CNN-Based Crack Identification System Using Different Preprocessing Algorithms.

Sensors (Basel, Switzerland)
The accurate intelligent identification and detection of road cracks is a key issue in road maintenance, and it has become popular to perform this task through the field of computer vision. In this paper, we proposed a deep learning-based crack detec...

Aeroengine Working Condition Recognition Based on MsCNN-BiLSTM.

Sensors (Basel, Switzerland)
Aeroengine working condition recognition is a pivotal step in engine fault diagnosis. Currently, most research on aeroengine condition recognition focuses on the stable condition. To identify the aeroengine working conditions including transition con...

Hybrid of deep learning and exponential smoothing for enhancing crime forecasting accuracy.

PloS one
The continued urbanization poses several challenges for law enforcement agencies to ensure a safe and secure environment. Countries are spending a substantial amount of their budgets to control and prevent crime. However, limited efforts have been ma...