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Zero-padding and spatial augmentation-based gas sensor node optimization approach in resource-constrained 6G-IoT paradigm
(MDPI, 2022-04-15)
Ultra-low-power is a key performance indicator in 6G-IoT ecosystems. Sensor nodes in this eco-system are also capable of running light-weight artificial intelligence (AI) models. In this work, we have achieved high performance ...
Machine learning for smart environments in B5G networks: connectivity and QoS
(Hindawi, 2021-09-20)
The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and ...
Data driven approach for eye disease classification with machine learning.
(MDPI, 2019-07-11)
Medical health systems have been concentrating on artificial intelligence techniques for
speedy diagnosis. However, the recording of health data in a standard form still requires attention so
that machine learning can ...
Fall detection system by machine learning framework for public health.
(Elsevier, 2018-11)
The elderly population is growing every year in Brazil. Consequently, health risks in elderly is a concern for public health system.
During the aging process, the mobility is affected, and falls are more frequent causing ...
An ensemble machine learning method for microplastics identification with FTIR spectrum
(Elsevier, 2022-06-20)
Microplastics (MPs) (size < 5 mm) marine pollution have been investigated and monitored by many researchers
and found in many coasts around the world. These toxic chemicals make their way into human diet through food ...
Convergence of machine learning and robotics communication in collaborative assembly: mobility, connectivity and future perpectives.
(Springer, 2019-10-16)
Collaborative assemblies of robots are promising the next generation of robot applications by ensuring that safe and reliable robots work collectively toward a common goal. To maintain this collaboration
and harmony, ...