687 research outputs found
Spectroscopic Analysis in the Virtual Observatory Environment with SPLAT-VO
SPLAT-VO is a powerful graphical tool for displaying, comparing, modifying
and analyzing astronomical spectra, as well as searching and retrieving spectra
from services around the world using Virtual Observatory (VO) protocols and
services. The development of SPLAT-VO started in 1999, as part of the Starlink
StarJava initiative, sometime before that of the VO, so initial support for the
VO was necessarily added once VO standards and services became available.
Further developments were supported by the Joint Astronomy Centre, Hawaii until
2009. Since end of 2011 development of SPLAT-VO has been continued by the
German Astrophysical Virtual Observatory, and the Astronomical Institute of the
Academy of Sciences of the Czech Republic. From this time several new features
have been added, including support for the latest VO protocols, along with new
visualization and spectra storing capabilities. This paper presents the history
of SPLAT-VO, it's capabilities, recent additions and future plans, as well as a
discussion on the motivations and lessons learned up to now.Comment: 15 pages, 6 figures, accepted for publication in Astronomy &
Computin
VR/Urban: spread.gun - design process and challenges in developing a shared encounter for media façades
Designing novel interaction concepts for urban environments is not only a technical challenge in terms of scale, safety, portability and deployment, but also a challenge of designing for social configurations and spatial settings. To outline what it takes to create a consistent and interactive experience in urban space, we describe the concept and multidisciplinary design process of VR/Urban's media intervention tool called Spread.gun, which was created for the Media Façade Festival 2008 in Berlin. Main design aims were the anticipation of urban space, situational system configuration and embodied interaction. This case study also reflects on the specific technical, organizational and infrastructural challenges encountered when developing media façade installations
MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception
This paper proposes an efficient multi-camera to Bird's-Eye-View (BEV) view
transformation method for 3D perception, dubbed MatrixVT. Existing view
transformers either suffer from poor transformation efficiency or rely on
device-specific operators, hindering the broad application of BEV models. In
contrast, our method generates BEV features efficiently with only convolutions
and matrix multiplications (MatMul). Specifically, we propose describing the
BEV feature as the MatMul of image feature and a sparse Feature Transporting
Matrix (FTM). A Prime Extraction module is then introduced to compress the
dimension of image features and reduce FTM's sparsity. Moreover, we propose the
Ring \& Ray Decomposition to replace the FTM with two matrices and reformulate
our pipeline to reduce calculation further. Compared to existing methods,
MatrixVT enjoys a faster speed and less memory footprint while remaining
deploy-friendly. Extensive experiments on the nuScenes benchmark demonstrate
that our method is highly efficient but obtains results on par with the SOTA
method in object detection and map segmentation task
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Drones: Innovative Technology for Use in Precision Pest Management.
Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early outbreak detection and treatment application are inherent to effective pest management, allowing management decisions to be implemented before pests are well-established and crop losses accrue. Pest monitoring is time-consuming and may be hampered by lack of reliable or cost-effective sampling techniques. Thus, we argue that an important research challenge associated with enhanced sustainability of pest management in modern agriculture is developing and promoting improved crop monitoring procedures. Biotic stress, such as herbivory by arthropod pests, elicits physiological defense responses in plants, leading to changes in leaf reflectance. Advanced imaging technologies can detect such changes, and can, therefore, be used as noninvasive crop monitoring methods. Furthermore, novel methods of treatment precision application are required. Both sensing and actuation technologies can be mounted on equipment moving through fields (e.g., irrigation equipment), on (un)manned driving vehicles, and on small drones. In this review, we focus specifically on use of small unmanned aerial robots, or small drones, in agricultural systems. Acquired and processed canopy reflectance data obtained with sensing drones could potentially be transmitted as a digital map to guide a second type of drone, actuation drones, to deliver solutions to the identified pest hotspots, such as precision releases of natural enemies and/or precision-sprays of pesticides. We emphasize how sustainable pest management in 21st-century agriculture will depend heavily on novel technologies, and how this trend will lead to a growing need for multi-disciplinary research collaborations between agronomists, ecologists, software programmers, and engineers
BroadBEV: Collaborative LiDAR-camera Fusion for Broad-sighted Bird's Eye View Map Construction
A recent sensor fusion in a Bird's Eye View (BEV) space has shown its utility
in various tasks such as 3D detection, map segmentation, etc. However, the
approach struggles with inaccurate camera BEV estimation, and a perception of
distant areas due to the sparsity of LiDAR points. In this paper, we propose a
broad BEV fusion (BroadBEV) that addresses the problems with a spatial
synchronization approach of cross-modality. Our strategy aims to enhance camera
BEV estimation for a broad-sighted perception while simultaneously improving
the completion of LiDAR's sparsity in the entire BEV space. Toward that end, we
devise Point-scattering that scatters LiDAR BEV distribution to camera depth
distribution. The method boosts the learning of depth estimation of the camera
branch and induces accurate location of dense camera features in BEV space. For
an effective BEV fusion between the spatially synchronized features, we suggest
ColFusion that applies self-attention weights of LiDAR and camera BEV features
to each other. Our extensive experiments demonstrate that BroadBEV provides a
broad-sighted BEV perception with remarkable performance gains
FB-BEV: BEV Representation from Forward-Backward View Transformations
View Transformation Module (VTM), where transformations happen between
multi-view image features and Bird-Eye-View (BEV) representation, is a crucial
step in camera-based BEV perception systems. Currently, the two most prominent
VTM paradigms are forward projection and backward projection. Forward
projection, represented by Lift-Splat-Shoot, leads to sparsely projected BEV
features without post-processing. Backward projection, with BEVFormer being an
example, tends to generate false-positive BEV features from incorrect
projections due to the lack of utilization on depth. To address the above
limitations, we propose a novel forward-backward view transformation module.
Our approach compensates for the deficiencies in both existing methods,
allowing them to enhance each other to obtain higher quality BEV
representations mutually. We instantiate the proposed module with FB-BEV, which
achieves a new state-of-the-art result of 62.4\% NDS on the nuScenes test set.
The code will be released at \url{https://github.com/NVlabs/FB-BEV}.Comment: Accept to ICCV 202
Development of wireless network planning software for rural community use
Rural New Zealand has poor access to broadband Internet. The CRCnet project at the University of Waikato identified point-to-point wireless technology as an appropriate solution, and built networks for rural communities. The project identified viable solutions using low-cost wireless technologies and commodity hardware, allowing them to establish general construction guidelines for planning rural wireless networks. The CRCnet researchers speculated that these general construction guidelines had simplified the wireless network problem to a point at which it seemed feasible to embed the guidelines within a software tool. A significant observation by the CRCnet researchers was that community members are collectively aware of much of the local information that is required in the planning process. Bringing these two ideas together, this thesis hypothesises that a software tool could be designed to enable members of rural communities to plan their own wireless networks.
To investigate this hypothesis, a wireless network planning system (WiPlan) was developed. WiPlan includes a tutorial that takes the unique approach of teaching the user process rather than the detail of network planning. WiPlan was evaluated using a novel evaluation technique structured as a roleplaying game. The study design provided participants with local knowledge appropriate for their planning roles. In two trials, WiPlan was found to support participants in successfully planning feasible networks, soliciting local knowledge as needed throughout the planning process. Participants in both trials were able to use the techniques introduced by the tutorial while planning their wireless network and successfully plan feasible wireless networks within budget in both study trials. This thesis explores the feasibility of designing a wireless networking planning tool, that can assist members of rural communities with no expertise in wireless network planning, to plan a feasible network and provides reasonable evidence to support the claim that such a planning tool is feasible
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