DeepCNN2023: Exploring Deep Convolutional Neural Networks Online Da Nang, Viet Nam, March 28-29, 2024 |
Conference website | https://sites.google.com/view/dcnn2023/home |
Submission link | https://easychair.org/conferences/?conf=deepcnn2023 |
Abstract registration deadline | October 1, 2023 |
Submission deadline | December 30, 2023 |
In machine learning, Convolutional Neural Networks (CNN or ConvNet) are complex feed forward neural networks. CNNs are used for image classification and recognition because of its high accuracy. Deep convolutional neural networks (DCNN) are a type of artificial neural network (ANN) that are based on the idea of a convolutional architecture. They are used for image processing and computer vision tasks such as object detection, scene segmentation, and image classification. DCNNs are composed of multiple layers of neurons that are connected hierarchically, allowing for the extraction of increasingly complex features from an input image. DCNNs have become widely used in recent years due to their ability to process large amounts of data accurately. As opposed to traditional ANNs, DCNNs are able to learn representations of the data that are more appropriate for the task at hand. For example, a DCNN used for image classification can learn to recognize patterns in the input image indicative of the label it is trying to predict.The use of DCNNs is rapidly growing, with many researchers exploring new applications for them. DCNNs have been used to develop computer vision systems for autonomous vehicles, medical image analysis, and natural language processing. As technology advances, DCNNs will be used to solve an increasingly diverse range of problems.
Submission Guidelines and Dates
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Abstract Submission : 20th March, 2023
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Abstract Acceptance: 25th March, 2023
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Full Chapter Submission: 10th April, 20
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Chapter Acceptance: 15th April 2023
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Final Chapter Submission: 28th April, 2023
Guidelines For Abstract:
All the abstracts must be submitted via easychair Link:
At the time of ABSTRACT SUBMISSION, submit the following information:
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Title---Make sure that it matches, the core theme of the book
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Author details- Name, Department Name, Institute Name and Email Address
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Abstract --- Min 200-250 words
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6 Keywords
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Table of Contents- Tentative
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Guidelines For Chapter:
All Chapters should be min 30-40 Pages, without references and Plagiarism should be less than 20%. And min 50-90 References, English Language should be good. And should comprehensively cover the content.
List of Topics
Topics, not limited to the following are:
1. Deep convolutional neural networks in relation extraction
2. Deep convolutional neural networks in semantic analysis
3. Deep convolution network based model for drug interactions
4. Deep convolutional neural networks in medical imaging
5. Deep convolutional neural networks in autonomous vehicles
6. Development of decision making algorithm using Deep convolutional neural networks
7. Deep convolutional neural networks in robotics
8. Deep convolutional neural networks in style transfer
9. Models based on advanced Deep convolutional neural networks architecture
10. Optimization in Deep convolutional neural networks
11. Visualization and interpretation techniques for Deep convolutional neural networks
12. Adversarial attacks on Deep convolutional neural networks
13. Transfer learning study with Deep convolutional neural networks
14. Meta-learning approaches for Deep convolutional neural networks
15. Deep convolutional neural networks for object detection
16. Image classification using Deep convolutional neural networks
17. Video segmentation using Deep convolutional neural network
18. Deep Convolutional Neural Networks: Principles and Applications
19. Exploring the Possibilities of Deep Convolutional Neural Networks
20. Deep Convolutional Neural Networks: Principles, Architectures, and Applications
Editors
Arun Solanki, Assistant Professor, Department of Computer Science and Engineering, University School of Information and Communication Technology, Gautam Buddha University, Noida, India. asolanki@gbu.ac.in
Malini M Patil, Department of Computer Science and Engineering, R V Institute of Technology and Management Chaitanya Layout, 8th Phase, JP Nagar, Bangalore, drmalinimpatil@gmail.com
Anand Nayyar, Professor, Scientist, Vice-Chairman (Research), Director (IoT and Intelligent Systems Lab), School of Computer Science, Duy Tan University, Da Nang, Viet Nam. anandnayyar@duytan.edu.vn
Publication
DeepCNN2023 proceedings will be published by by Nova Publishers. Indexed in Google Scholar, Scopus
Contact
All questions about submissions should be emailed to : Anand Nayyar, Duy Tan University, Da Nang 550000. Email: anandnayyar@duytan.edu.vn; WhatsApp: +91-9878327635