Related papers: Multi-channel Sensor Network Construction, Data Fu…
The task of crowd counting in varying density scenes is an extremely difficult challenge due to large scale variations. In this paper, we propose a novel dual path multi-scale fusion network architecture with attention mechanism named…
The design and technology development of 6G-enabled networked intelligent systems needs an accurate real-time channel model as the cornerstone. However, with the new requirements of 6G-enabled networked intelligent systems, the conventional…
6G is envisaged to provide multimodal sensing, pervasive intelligence, global coverage, global coverage, etc., which poses extreme intricacy and new challenges to the network design and optimization. As the core part of 6G, wireless channel…
Multimodal visual information fusion aims to integrate the multi-sensor data into a single image which contains more complementary information and less redundant features. However the complementary information is hard to extract, especially…
Image fusion technology is widely used to fuse the complementary information between multi-source remote sensing images. Inspired by the frontier of deep learning, this paper first proposes a heterogeneous-integrated framework based on a…
The proliferation of artificial intelligence has enabled a diversity of applications that bridge the gap between digital and physical worlds. As physical environments are too complex to model through a single information acquisition…
Intelligent operation of thermal energy networks aims to improve energy efficiency, reliability, and operational flexibility through data-driven control, predictive optimization, and early fault detection. Achieving these goals relies on…
This work investigates Distributed Detection (DD) in Wireless Sensor Networks (WSNs) utilizing channel-aware binary-decision fusion over a shared flat-fading channel. A reconfigurable metasurface, positioned in the near-field of a limited…
Existing work in intelligent communications has recently made preliminary attempts to utilize multi-source sensing information (MSI) to improve the system performance. However, the research on MSI aided intelligent communications has not…
Autonomous driving demands accurate perception and safe decision-making. To achieve this, automated vehicles are now equipped with multiple sensors (e.g., camera, Lidar, etc.), enabling them to exploit complementary environmental context by…
We study multi-sensor fusion for 3D semantic segmentation that is important to scene understanding for many applications, such as autonomous driving and robotics. Existing fusion-based methods, however, may not achieve promising performance…
Smart living is a trending lifestyle that envisions lower energy consumption, sound public services, and better quality of life for human being. The Internet of Things (IoT) is a compelling platform connecting various sensors around us to…
Smart environments interconnect indoor building environments, indoor wireless sensor and actuator networks, smartphones, and human together to provide smart infrastructure management and intelligent user experiences. To enable the "smart"…
Consider the two related problems of sensor selection and sensor fusion. In the first, given a set of sensors, one wishes to identify a subset of the sensors, which while small in size, captures the essence of the data gathered by the…
We tackle a challenging task: multi-view and multi-modal event detection that detects events in a wide-range real environment by utilizing data from distributed cameras and microphones and their weak labels. In this task, distributed…
This article introduces the HYMN (HYbrid Multi-technology Navigation) dataset: a multi-system, and time synchronized dataset for localization research based on opportunistic signals collected in an indoor-outdoor scenario. HYMN comprises…
This paper presents a novel multimodal human activity recognition system. It uses a two-stream decision level fusion of vision and inertial sensors. In the first stream, raw RGB frames are passed to a part affinity field-based pose…
The pervasiveness of Wi-Fi signals provides significant opportunities for human sensing and activity recognition in fields such as healthcare. The sensors most commonly used for passive Wi-Fi sensing are based on passive Wi-Fi radar (PWR)…
The Internet of Things (IoT) could enable the development of cloud multiple-input multiple-output (MIMO) systems where internet-enabled devices can work as distributed transmission/reception entities. We expect that spatial multiplexing…
Sensor deployments in Smart Homes have long reached commercial relevance for applications such as home automation, home safety or energy consumption awareness and reduction. Nevertheless, due to the heterogeneity of sensor devices and…