Multi-task deep learning model for quantitative volatile organic compounds analysis by feature fusion of electronic nose sensing
In exploring pattern recognition for electronic noses via deep neural networks, traditional
networks encounter key challenges, such as low training efficiency, and neglect of spatial …
networks encounter key challenges, such as low training efficiency, and neglect of spatial …
A Survey of mmWave Radar-Based Sensing in Autonomous Vehicles, Smart Homes and Industry
Sensing technology plays a crucial role in bridging the physical and digital worlds. By
transforming a multitude of physical phenomena into digital data, it significantly enhances …
transforming a multitude of physical phenomena into digital data, it significantly enhances …
A highly accurate and sensitive mmWave displacement-sensing Doppler radar with a quadrature-less edge-driven phase demodulator
A 110-mW 39-GHz Doppler radar front end in 65-nm CMOS for displacement and vibration
sensing is proposed. Conventional Doppler radar suffers from detection nulls, at which the …
sensing is proposed. Conventional Doppler radar suffers from detection nulls, at which the …
Multi-Sensor-Based Action Monitoring and Recognition via Hybrid Descriptors and Logistic Regression
In the fields of body-worn sensors and computer vision, current research is being done to
track and detect falls and activities of daily living using the automatic recognition of human …
track and detect falls and activities of daily living using the automatic recognition of human …
Automotive radar processing with spiking neural networks: Concepts and challenges
Frequency-modulated continuous wave radar sensors play an essential role for assisted
and autonomous driving as they are robust under all weather and light conditions. However …
and autonomous driving as they are robust under all weather and light conditions. However …
End-to-end dynamic gesture recognition using mmWave radar
Millimeter-wave (mmWave) radar sensors are a promising modality for gesture recognition
as they can overcome several limitations of optic sensors typically used for gesture …
as they can overcome several limitations of optic sensors typically used for gesture …
Extended liquid state machines for speech recognition
A liquid state machine (LSM) is a biologically plausible model of a cortical microcircuit. It
exists of a random, sparse reservoir of recurrently connected spiking neurons with fixed …
exists of a random, sparse reservoir of recurrently connected spiking neurons with fixed …
On the use of spiking neural networks for ultralow-power radar gesture recognition
Radar processing via spiking neural networks (SNNs) has recently emerged as a solution in
the field of ultralow-power wireless human–computer interaction. Compared to traditional …
the field of ultralow-power wireless human–computer interaction. Compared to traditional …
Aircraft marshaling signals dataset of fmcw radar and event-based camera for sensor fusion
The advent of neural networks capable of learning salient features from radar data has
expanded the breadth of radar applications, often as an alternative sensor or a …
expanded the breadth of radar applications, often as an alternative sensor or a …
Improving human activity classification based on micro-doppler signatures of FMCW radar with the effect of noise
Nowadays, classifying human activities is applied in many essential fields, such as
healthcare, security monitoring, and search and rescue missions. Radar sensor-based …
healthcare, security monitoring, and search and rescue missions. Radar sensor-based …