Search results for " processing"
showing 10 items of 7549 documents
Structured Output SVM for Remote Sensing Image Classification
2011
Traditional kernel classifiers assume independence among the classification outputs. As a consequence, each misclassification receives the same weight in the loss function. Moreover, the kernel function only takes into account the similarity between input values and ignores possible relationships between the classes to be predicted. These assumptions are not consistent for most of real-life problems. In the particular case of remote sensing data, this is not a good assumption either. Segmentation of images acquired by airborne or satellite sensors is a very active field of research in which one tries to classify a pixel into a predefined set of classes of interest (e.g. water, grass, trees,…
SREP: An Energy Efficient Relay Protocol for Wireless Sensor Networks
2018
While wireless sensor networks continue to break new grounds in applications, favored by technological innovations, energy efficiency continues to stagnate. Duty cycling remains the most popular and effective technique used to improve energy efficiency and thus lifetime of the network. Nevertheless, duty cycling imposes temporary unavailability on the network leading to deterioration of quality of service. To take care of this rather contradicting reality, this paper proposes Sleep Relay Protocol (SREP). Network nodes are divided into sets according to their location and the sets sleep in relay within a duty cycle period. Two set formation algorithms are proposed at initiation of our propos…
Deep Learning-Based Real-Time Object Detection in Inland Navigation
2019
International audience; Semi-autonomous and fully-autonomous systems must have knowledge about the objects in their environment to ensure a safe navigation. Modern approaches implement deep learning techniques to train a neural network for object detection. This project will study the effectiveness of using several promising algorithms such as Faster R-CNN, SSD, and different versions of YOLO, to detect, classify, and track objects in near real-time fluvial domain. Since no dataset is available for this purpose in literature, we first started by annotating a dataset of 2488 images with almost 35 400 annotations for training the convolutional neural network architectures. We made this data s…
Open Set Audio Classification Using Autoencoders Trained on Few Data.
2020
Open-set recognition (OSR) is a challenging machine learning problem that appears when classifiers are faced with test instances from classes not seen during training. It can be summarized as the problem of correctly identifying instances from a known class (seen during training) while rejecting any unknown or unwanted samples (those belonging to unseen classes). Another problem arising in practical scenarios is few-shot learning (FSL), which appears when there is no availability of a large number of positive samples for training a recognition system. Taking these two limitations into account, a new dataset for OSR and FSL for audio data was recently released to promote research on solution…
Energy Conscious Building Design
1987
Since the beginning of energy crisis many design tools have been developed in order to enable the designer to cope with energy consumption in buildings. These tools are of different kind: from very sophisticated simulation models to simplified (often too much) methods. Each of them offers various advantages and disadvantages, and it is up to the designer to choose among them.
SINR analysis of OFDM systems using a geometry-based underwater acoustic channel model
2015
The Doppler effect is caused by the relative movement between the transmitter (Tx) and the receiver (Rx) and/or the surface motion (waves) in underwater acoustic (UWA) communication systems. The inter-channel interference (ICI) caused by the Doppler effect degrades the performance of orthogonal frequency-division multiplexing (OFDM) systems over UWA channels. This paper is devoted to the ICI plus noise analysis of UWA-OFDM systems over a geometry-based channel model for shallow UWA channels. We carry out the exact calculation of the ICI power, ambient noise power, and required transmit power, as well as their effects on the performance of UWA-OFDM systems. The signal-to-interference ratio (…
Application of Model Predictive Control in Discrete Displacement Cylinders to Drive a Knuckle Boom Crane
2018
In this paper, two Discrete Displacement Cylinders (DDCs) are used to drive the boom of a knuckle boom crane. DDCs operate by connecting one of several available pressure levels to each chamber in order to produce different forces. A trade-off exists with such systems, between the accuracy of tracking and energy dissipation due to switching. A popular way to approach this problem is a Force Shifting Algorithm (FSA). However, in this paper, the trade-off is managed by use of a Model Predictive Control (MPC) algorithm. The tracking accuracy and energy efficiency of the MPC and FSA strategies for DDCs are compared to a PID strategy for standard cylinders. The comparison is obtained by use of a…
Automatic fringe pattern enhancement using truly adaptive period-guided bidimensional empirical mode decomposition.
2020
Fringe patterns encode the information about the result of a measurement performed via widely used optical full-field testing methods, e.g., interferometry, digital holographic microscopy, moiré techniques, structured illumination etc. Affected by the optical setup, changing environment and the sample itself fringe patterns are often corrupted with substantial noise, strong and uneven background illumination and exhibit low contrast. Fringe pattern enhancement, i.e., noise minimization and background term removal, at the pre-processing stage prior to the phase map calculation (for the measurement result decoding) is therefore essential to minimize the jeopardizing effect the mentioned error…
Full-parallax 3D display from stereo-hybrid 3D camera system
2018
Abstract In this paper, we propose an innovative approach for the production of the microimages ready to display onto an integral-imaging monitor. Our main contribution is using a stereo-hybrid 3D camera system, which is used for picking up a 3D data pair and composing a denser point cloud. However, there is an intrinsic difficulty in the fact that hybrid sensors have dissimilarities and therefore should be equalized. Handled data facilitate to generating an integral image after projecting computationally the information through a virtual pinhole array. We illustrate this procedure with some imaging experiments that provide microimages with enhanced quality. After projection of such microim…
Dynamic 3D Scene Reconstruction and Enhancement
2017
International audience; In this paper, we present a 3D reconstruction and enhancement approach for high quality dynamic city scene reconstructions. We first detect and segment the moving objects using 3D Motion Segmenta-tion approach by exploiting the feature trajectories' behaviours. Getting the segmentations of both the dynamic scene parts and the static scene parts, we propose an efficient point cloud registration approach which takes the advantages of 3-point RANSAC and Iterative Closest Points algorithms to produce precise point cloud alignment. Furthermore, we proposed a point cloud smoothing and texture mapping framework to enhance the results of reconstructions for both the static a…