Héctor Migallón

Monitoring Pest Insect Traps by Means of Low-Power Image Sensor Technologies

Monitoring pest insect populations is currently a key issue in agriculture and forestry protection. At the farm level, human operators typically must perform periodical surveys of the traps disseminated through the field. This is a labor-, time- and cost-consuming activity, in particular for large plantations or large forestry areas, so it would be of great advantage to have an affordable system capable of doing this task automatically in an accurate and a more efficient way. This paper proposes an autonomous monitoring system based on a low-cost image sensor that it is able to capture and send images of the trap contents to a remote control station with the periodicity demanded by the trapping application. Our autonomous monitoring system will be able to cover large areas with very low energy consumption. This issue would be the main key point in our study; since the operational live of the overall monitoring system should be extended to months of continuous operation without any kind of maintenance (i.e., battery replacement). The images delivered by image sensors would be time-stamped and processed in the control station to get the number of individuals found at each trap. All the information would be conveniently stored at the control station, and accessible via Internet by means of available network services at control station (WiFi, WiMax, 3G/4G, etc.).

Slice-based parallel approach for HEVC encoder

The high efficiency video coding (HEVC) is the newest video coding standard from the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group, which significantly increases the computing demands to encode video to reach the limits on compression efficiency. Our interest is centered on applying parallel processing techniques to HEVC encoder to significantly reduce the computational time without disturbing the coding performance behavior. We propose a parallelization approach to the HEVC encoder which is well suited to multicore architectures. Our proposal uses OpenMP programming paradigm working at slice parallelization level. We encode several slices of each frame at the same time using all available processing cores. The results show that speed-ups up to

Alternating two-stage methods for consistent linear systems with applications to the parallel solution of Markov chains

9.8

GPU-based 3D lower tree wavelet video encoder

9.8 can be obtained for the All Intra mode and up to

PyPnetCDF: A high level framework for parallel access to netCDF files

8.7

Parallel alternating iterative algorithms with and without overlapping on multicore architectures

8.7 for Low-Delay B, Low-Delay P and Random Access modes for