Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=7361 ...

Abstract: In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models ...

Abstract: The adoption of voluntary environmental standards has emerged as a promising approach to coping with climate change and achieving sustainable development. While prior research has ...

Abstract: Construction quality management (CQM), as one of the major activities in construction project management, relies heavily on knowledge. Unfortunately, the knowledge of CQM is diverse in ...

Abstract: Change detection (CD) is an essential aspect of urban planning and resource management. Deep learning (DL) has the potential to detect complex changes from massive data more automatically ...

Abstract: This brief presents a 12-bit low-power successive-approximation-register (SAR) capacitance-to-digital converter (CDC) for capacitive pressure sensors. It adopts a capacitance-to-voltage ...

Abstract: Radar transmits active agile waveformplays a significant role in anti-jamming. However, efficient coherent integration of target's agile echo in a coherent processing interval (CPI) usually ...

Abstract: Recent studies have shown that the deep domain adaptation (DA) technique has achieved remarkable results in cross-domain hyperspectral image (HSI) classification task. However, these DA ...

Abstract: With the continuous development of intelligent UAV technology, efficient and accurate sensing of surrounding objects through onboard sensors has become an important research direction. Among ...

Abstract: Considerable interindividual variability exists in electroencephalogram (EEG) signals, resulting in challenges for subject-independent emotion recognition tasks. Current research in ...

Abstract: Deep learning models have been widely investigated for computing and analyzing brain images across various downstream tasks such as disease diagnosis and age regression. Most existing models ...