Self-organization mechanisms have been investigated and developed to efficiently operate networked embedded systems. Special focus was given to wireless sensor networks (WSN) and sensor/actuator networks (SANET). Looking at the most pressing issues in such networks, the limited resources and the huge amount of interoperating nodes, the proposed solutions primarily intend to solve the scalabilit...

Actual research projects in the field of wireless communication systems focus on distributed, heterogeneous architectures for advanced Sensor-Actor-Networks (SANETs). Each subsystem provides specific capabilities for measuring or manipulating its environment. At the same time, a huge amount of sensor, status and control data has to be transmitted over different network interfaces and communicat...

Deep learning is now receiving widespread attention in hyperspectral image (HSI) classification. However, due to the imbalance between a huge number of weights and limited training samples, many problems difficulties have arisen from use deep methods HSI To handle this issue, an efficient learning-based classification method, namely, spatial-aware network (SANet) has been proposed paper. The ma...

Assigning geospatial objects with specific categories at the pixel level is a fundamental task in remote sensing image analysis. Along rapid development of sensor technologies, remotely sensed images can be captured multiple spatial resolutions (MSR) information content manifested different scales. Extracting from these MSR represents huge opportunities for enhanced feature representation and c...

Change detection (CD) is one of the important applications remote sensing and plays an role in disaster assessment, land use detection, urban sprawl tracking. High-accuracy fully supervised methods are main for CD tasks at present. However, these require a large amount labeled data consisting bi-temporal images their change maps. Moreover, creating maps takes lot labor time. To address this lim...

This chapter paper considers GI System-based methods for analyzing spatial phenomena that occur on a network, herein referred to as network spatial phenomena. A typical network spatial phenomenon is the incidence of traffic accidents that occur on a road network (additional examples are given in Section 1). To analyze network spatial phenomena properly, a new class of spatial methods has been i...