Deep Neural Network (DNN) has gained unprecedented performance due to its automated
feature extraction capability. This high order performance leads to significant incorporation …

Deep Neural Networks (DNNs) have gained unprecedented popularity due to their high-
order performance and automated feature extraction capability. This has encouraged …

Human activity recognition (HAR) is a key enabling technology for a wide range of emerging
applications. Although multimodal sensing systems are essential for capturing complex and …

With the development of the Internet of Things (IoT), many kinds of wireless signals (eg, Wi-
Fi, LoRa, RFID) are filling our living and working spaces nowadays. Beyond communication …

While decade-long research has clearly demonstrated the vast potential of radio frequency
(RF) for many human sensing tasks, scaling this technology to large scenarios remained …

After many years of decline, hunger in Africa is growing again. This represents a global
societal issue that all disciplines concerned with data analysis are facing. The rapid and …

With the transformation and upgrading of the manufacturing industry, manufacturing systems
have become increasingly complex in terms of the structural functionality, process flows …

The paper enhances deep-neural-network-based inference in sensing applications by
introducing a lightweight attention mechanism called the global attention module for multi …

Recently, significant efforts are made to explore device-free human activity recognition
techniques that utilize the information collected by existing indoor wireless infrastructures …

Automatically recognizing a broad spectrum of human activities is key to realizing many
compelling applications in health, personal assistance, human-computer interaction and …