Search results for "InGaN"
showing 10 items of 1214 documents
Seed Bank in Annuals: Competition Between Banker and Non-banker Morphs
2002
Seed bank is a plant life history strategy against the unpredictability of the biotic and the abiotic environment. We simulated competition between a seed banking and a non-banking morph of an annual plant. A constant fraction of the banker morph seeds was allocated to the seed bank, where they had a constant mortality and germination rate. All surviving seeds of the non-banker morph germinated in the next generation. The seedlings of both morphs experienced similar density-dependent mortality. Whether one of the morphs wins or the morphs coexist was evaluated from parameter space plots and statistically with logistic regression analysis. All parameters of the model had a significant, nonli…
Massively Parallel ANS Decoding on GPUs
2019
In recent years, graphics processors have enabled significant advances in the fields of big data and streamed deep learning. In order to keep control of rapidly growing amounts of data and to achieve sufficient throughput rates, compression features are a key part of many applications including popular deep learning pipelines. However, as most of the respective APIs rely on CPU-based preprocessing for decoding, data decompression frequently becomes a bottleneck in accelerated compute systems. This establishes the need for efficient GPU-based solutions for decompression. Asymmetric numeral systems (ANS) represent a modern approach to entropy coding, combining superior compression results wit…
Massively Parallel Huffman Decoding on GPUs
2018
Data compression is a fundamental building block in a wide range of applications. Besides its intended purpose to save valuable storage on hard disks, compression can be utilized to increase the effective bandwidth to attached storage as realized by state-of-the-art file systems. In the foreseeing future, on-the-fly compression and decompression will gain utmost importance for the processing of data-intensive applications such as streamed Deep Learning tasks or Next Generation Sequencing pipelines, which establishes the need for fast parallel implementations. Huffman coding is an integral part of a number of compression methods. However, efficient parallel implementation of Huffman decompre…
A segmentation algorithm for noisy images
2005
International audience; This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have studied how noise affects the performance of the algorithm. The alpha-stable noise is considered and its effects on the algorithm are studied. Key words : graph, hypergraph, neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation and noise removal.
Optimization of 3-DOF Parallel Motion Devices for Low-Cost Vehicle Simulators
2017
Motion generation systems are becoming increasingly important in certain Virtual Reality (VR) applications, such as vehicle simulators. This paper deals with the analysis of the Inverse Kinematics (IK) and the reachable workspace of a three-degrees-of-freedom (3-DOF) parallel manipulator, proposing different transformations and optimizations in order to simplify its use with Motion Cueing Algorithms (MCA) for self-motion generation in VR simulators. The proposed analysis and improvements are performed on a 3-DOF heave-pitch-roll manipulator with rotational motors, commonly used for low-cost motion-based commercial simulators. The analysis has been empirically validated against a real 3-DOF …
LMI-based 2D-3D Registration: from Uncalibrated Images to Euclidean Scene
2015
International audience; This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates , and two or more uncalibrated cameras. An unknown subset of the scanned points have their image projections detected and matched across images. The proposed approach assumes the cameras only known in some arbitrary projective frame and no calibration or autocalibration is required. The devised solution is based on a Linear Matrix Inequality (LMI) framework that allows simultaneously estimating the projective transformation relating the cameras to the scene and establishing 2D-3D correspondences without triangulating image points. The proposed LMI framewo…
Adaptive Backstepping Control of Nonlinear Uncertain Systems With Quantized States
2019
This paper investigates the stabilization problem for uncertain nonlinear systems with quantized states. All states in the system are quantized by a static bounded quantizer, including uniform quantizer, hysteresis-uniform quantizer, and logarithmic-uniform quantizer as examples. An adaptive backstepping-based control algorithm, which can handle discontinuity, resulted from the state quantization and a new approach to stability analysis are developed by constructing a new compensation scheme for the effects of the state quantization. Besides showing the global ultimate boundedness of the system, the stabilization error performance is also established and can be improved by appropriately adj…
Rotation estimation and vanishing point extraction by omnidirectional vision in urban environment
2012
International audience; Rotation estimation is a fundamental step for various robotic applications such as automatic control of ground/aerial vehicles, motion estimation and 3D reconstruction. However it is now well established that traditional navigation equipments, such as global positioning systems (GPSs) or inertial measurement units (IMUs), suffer from several disadvantages. Hence, some vision-based works have been proposed recently. Whereas interesting results can be obtained, the existing methods have non-negligible limitations such as a difficult feature matching (e.g. repeated textures, blur or illumination changes) and a high computational cost (e.g. analyze in the frequency domai…
Vision based attitude and altitude estimation for UAVs in dark environments
2011
This paper presents a system dedicated to the real-time estimation of attitude and altitude for unmanned aerial vehicles (UAV) under low light and dark environment. This system consists in a fisheye camera, which allows to cover a large field of view (FOV), and a laser circle projector mounted on a fixed baseline. The approach, close to structured light systems, uses the geometrical information obtained by the projection of the laser circle onto the ground plane and perceived by the camera. We present a theoretical study of the system in which the camera is modelled as a sphere and show that the estimation of a conic on this sphere allows to obtain the attitude and the altitude of the robot…
Omnidirectional vision for UAV: applications to attitude, motion and altitude estimation for day and night conditions
2012
International audience; This paper presents the combined applications of omnidirectional vision featuring on its application to aerial robotics. Omnidirectional vision is first used to compute the attitude, altitude and motion not only in rural environment but also in the urban space. Secondly, a combination of omnidirectional and perspective cameras permits to estimate the altitude. Finally we present a stereo system consisting of an omnidirectional camera with a laser pattern projector enables to calculate the altitude and attitude during the improperly illuminated conditions to dark environments. We demonstrate that omnidirectional camera in conjunction with other sensors is suitable cho…