3D visual analysis of seabed on smartphone
April 04, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Zhihan Lv, Tianyun Su, Xiaoming Li, Shengzhong Feng
arXiv ID
1504.01049
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.GR
Citations
13
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We create a 'virtual-seabed' platform to realize the 3D visual analysis of seabed on smartphone. The 3D seabed platform is based on a 'section-drilling' model, implementing visualization and analysis of the integrated data of seabed on the 3D browser on smartphone. Some 3D visual analysis functions are developed. This work presents a thorough and interesting way of presenting seabed data on smartphone, which raises many application possibilities. This platform is another practical proof based on our WebVRGIS platform.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted