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Wireless Sensor Network (WSN) is a system used to conduct a remote monitoring in a wide monitoring area. It has a sensor node — a sampling point — which communicate each other to passing their data to central node for recapitulation or transmit it to data center. Because of that, communication system is a crucial thing for WSN. However, WSN may be deployed in a environment that far from ideal condition...
Wireless Sensor Network (WSN) is a system that have a capability to conduct data acquisition and monitoring in a wide sampling area for a long time. However, because of its big-scale monitoring, amount of data accumulated from WSN is very huge. Conventional database system may not be able to handle its big amount of data. To overcome that, big data approach is used for an alternative data storage...
This research aims to improve the capability of semantic segmentation through data perspective. This research proposed a parameterized Conditional Random Fields model and learns the model by using Structured Support Vector Machine (SSVM). The SSVM utilizes Hamming loss function for optimizing 1-slack Margin Rescaling formulation. The joint feature vector is derived from energy potentials. Variation...
Carbon Dioxide gas (CO2) gas contained in our air which has many roles in environment, but in a huge amount it became dangerous. To encounter that, the system for CO2 monitoring is needed. One of the most effective way is using Wireless Sensor Network (WSN). This system capable to monitor concentration of CO2 and another variable using sensor nodes. But not all of that parameters is correlated to...
The growth of data has bring us to the big data generation where the amount of data cannot be computed using conventional environment. There are a lot of computational environment that had been developed to compute big data, one of them is Hadoop that has Distributed File System and MapReduce framework. Spark is newly framework that can be combined with Hadoop and run on top of it. In this paper,...
Traffic congestion is a problem that often occurs in the big cities in Indonesia. It is caused by very rapid increase of vehicle. The offered solution is to monitor the traffic situation automatically. We implemented the method of detecting vehicle during night in four single board computers (SBC) that are: Raspberry Pi B+, Beagleboard Xm, Raspberry Pi 2 and Odroid XU4. Perfomance of Odroid XU4 exceed...
Semantic segmentation is an image labeling process for each pixels according to defined objects class and its presence in an image. Labeling process consists of recognizing, detecting location and labeling pixels that defines the object in the image. Annotation result of semantic segmentation needs ground truth to verify accuracy of score prediction. Therefore, this research propose a model to predict...
One promising approach for pixel-wise semantic segmentation is based on higher-order Conditional Random Fields (CKFs). We aim to selectively choose segments for the higher-order CRFs in semantic segmentation. To this end, we formulate the selection as an optimization problem. We propose three optimization criteria in relation to the selected segments, namely: a) averaged goodness, b) coverage area...
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