In this work, we address the human parsing task with a novel Contextualized Convolutional
Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global …

This paper develops a new framework for distributed coding and compression in sensor
networks based on distributed compressed sensing (DCS). DCS exploits both intra-signal …

Due to the wireless nature of communication in sensor networks, the communication
patterns between sensors could be leaked regardless of the adoption of encryption …

The nature of wireless sensor networks necessitates specific design requirements, of which
energy efficiency is paramount. In this paper we present SEER (Simple Energy Efficient …

Applications of Wireless Sensor devices are widely used by various monitoring sections
such as environmental monitoring, industrial sensing, habitat modeling, healthcare and …

Unlike conventional sensor networks, wireless sensors are limited in power, have much
smaller memory buffers, and possess relatively slower processing speeds. These …

In this paper, we propose a tree based regression algorithm,(TREG) that addresses the
problem of data compression in wireless sensor networks. By function approximation based …

Using the previously developed concepts of semantic spacetime, I explore the interpretation
of knowledge representations, and their structure, as a semantic system, within the …

For data-collection applications in sensor networks, it is important to ensure base station
receives a complete picture about the monitored area. Convergecast is an important …

A sensor network consists of a set of battery-powered nodes, which collaborate to perform
sensing tasks in a given environment. It may contain one or more base stations to collect …