CRC-OD2021: Object Detection with Deep Learning Models: Principles and Applications |
Submission link | https://easychair.org/conferences/?conf=crcod2021 |
Abstract registration deadline | May 15, 2021 |
Submission deadline | August 31, 2021 |
Object Detection with Deep Learning Models: Principles and Applications
IntroductionReal-time object detection in computer vision is challenging and demands efficient solutions. The computer vision system takes the scene information as an image and tries to find objects in it. This is suffered from the resolution and location invariant issues where the object is presented in different resolutions and locations. The computer vision aggregates different outputs of object detection into a single unit and tries to generalize it before deep learning comes. After the deep learning presence in object detection the resolution and location invariant issues were resolved and brought significant results in the field. Many networks have been developed for various kinds of object detection in computer vision. It brought different stages of learning to facilitate different levels of feature detection in an image. Now, deep learning-based object detection becomes popular and it is being applied in a variety of fields such as scene understanding, human-computer interaction, robotics, vehicle navigation, video surveillance, self-driving systems, transportation, and healthcare systems. Sensors are mainly deployed in all the fields to acquire the information that generates petabytes of image data in a few hours. These data will be reduced and integrated with other related data to get clear content of the current data. It uses object detection techniques to detect various objects such as people, vehicles, faces, intruders, and any object of interest from the raw imagery data. Detecting facial masks, the social distance between the peoples, detecting and locating the wildfire in the territory of forest zones, detecting the vehicles parked in non-parking areas, obstacle detection in the autonomous deriving system, and detecting unattended baggage in public places are some applications of object detection.This book is mainly for bringing all the related researches in different fields under the single umbrella of deep learning-based object detection in computer vision. The main focus is to integrate all the developments in the object detection of computer vision using deep learning. It starts from frameworks and moves to services, benchmarked datasets, application domains, and recent development in deep learning for object detection.
Tracks
1. Introduction: Deep Learning and Computer Vision
2. Object Detection Frameworks and Services in Computer Vision
3. Challenges and survey of Datasets for Object Detection in Computer Vision
4. Deep Learning-based Intruder detection through video surveillance
5. Optical character recognition from documents using CNN
6. Obstacle detection and control of autonomous vehicle's navigation using Deep Learning
7. Vision-guided simultaneous localization and mapping
8. Automatic detection of consignments labels using Deep Learning
9. Deep Learning Solutions for Vehicle number plate identification and recognition
10. Brain Tumor identification in MRI Scan Images using CNN Models
11. Deep Learning-based Anomaly detection cervical spine radiography
12. Human face identification and recognition from crowd images using CNN
13. AI guided visual inspection for defect identification
14. Object identification and localization for robots
15. Deep Learning Solutions for Pest Identification in Agriculture
16. Image fusion for Augmented Reality
17. Deep Learning for Classification of objects from remote sensing images
18. Real-time object detection and measurement from 3D Imaging
Submission Link: https://easychair.org/conferences/?conf=crcod2021
Important Date(s):
Abstract Submission Deadline: 15 May 2021
Full Chapter Submission: 31 Aug 2021
Editor(s)
1. Dr.S.Poonkuntran, Velammal College of Engineering and Technology, India
2. Dr. Rajesh Kumar Dhanraj, Galgotias University, India.
3. Dr Balamurugan Balusamy, Galgotias University, India
Publisher: CRC Press - A Taylor and Francis
Contact: .Dr.S.Poonkuntran - s.poonkuntran@gmail.com