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Geometry and Vision : First International Symposium, ISGV 2021, Auckland, New Zealand, January 28-29, 2021, Revised Selected Papers / edited by Minh Nguyen, Wei Qi Yan, Harvey Ho.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Communications in computer and information science 1865-0937 ; 1386
- Communications in Computer and Information Science, 1865-0937 ; 1386
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computer vision.
- Computer engineering.
- Computer networks.
- Social sciences-Data processing.
- Education-Data processing.
- Artificial Intelligence.
- Computer Vision.
- Computer Engineering and Networks.
- Computer Application in Social and Behavioral Sciences.
- Computers and Education.
- Local Subjects:
- Artificial Intelligence.
- Computer Vision.
- Computer Engineering and Networks.
- Computer Application in Social and Behavioral Sciences.
- Computers and Education.
- Physical Description:
- 1 online resource (XIII, 394 pages) : 222 illustrations, 173 illustrations in color.
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2021.
- System Details:
- text file PDF
- Summary:
- This book constitutes selected papers from the First International Symposium on Geometry and Vision, ISGV 2021, held in Auckland, New Zealand, in January 2021. Due to the COVID-19 pandemic the conference was held in partially virtual format. The 29 papers were thoroughly reviewed and selected from 50 submissions. They cover topics in areas of digital geometry, graphics, image and video technologies, computer vision, and multimedia technologies.
- Contents:
- A New Noise Generating Method Based onGaussian Sampling for Privacy Preservation
- Traffic-Sign Recognition Using Deep Learning
- Tree Leaves Detection Based on Deep Learning
- Deep Learning in Medical Applications: Lesion Segmentation in Skin Cancer Images using Modified and Improved Encoder-Decoder Architecture
- Apple Ripeness Identification Using Deep Learning
- A Hand-Held Sensor System for Exploration and Thermal Mapping of Volcanic Fumarole Fields
- Traffic Sign Recognition Using Guided Image Filtering
- Towards a generic Bicubic Hermite meshtemplate for cow udders
- Sign Language Recognition from Digital Videos Using Deep Learning Methods
- New Zealand Shellfish Detection, Recognitionand Counting: a Deep Learning Approach on Mobile Devices
- Coverless Video Steganography Based on Inter Frame Combination
- Character Photo Selection for Mobile Platform
- Close Euclidean Shortest Path Crossing an Ordered 3D Skew Segment Sequence
- A lane line detection algorithm based on convolutional neural network
- Segment-and Arc-based Vectorizations by Multi-scale/Irregular Tangential Covering
- Algorithms for Computing TopologicalInvariants in Digital Spaces
- Discrete Linear Geometry on Non-Square Grid
- Electric scooter and its rider detection framework based on deep learning for supporting scooter-related injury emergency services
- Tracking Livestock using a Fully Connected Network and Kalman Filter
- A Comparison of Approaches for Synchronizing Events in Video Streams Using Audio
- Union-Retire: A New Paradigm for Single-Pass Connected Component Analysis
- Improving Object Detection in Real-world Traffic Scenes
- Comparison of Red versus Blue Laser Light forAccurate 3D Measurement of Highly Specular Surfaces in Ambient Lighting Conditions
- Fruit Detection from Digital Images Using CenterNet
- A Graph-regularized Non-local Hyperspectral Image Denoising Method
- Random convolutional network for hyperspectra limage classification
- MamboNet: Adversarial Semantic Segmentation for Autonomous Driving
- Effective Pavement Crack Delineation using a Cascaded Dilation Module and Fully Convolutional Networks
- D-GaussianNet: Adaptive Distorted Gaussian Matched Filter with Convolutional Neural Network for Retinal Vessel Segmentation. .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-72073-5
- 9783030720735
- Access Restriction:
- Restricted for use by site license.
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