Author(s):
1. Asiya Jan:
Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture,Peshawar,Pakistan
2. Javed Iqbal Bangash:
Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture,Peshawar,Pakistan
3. Nouman Atta:
Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture,Peshawar,Pakistan
4. Maliha Tahir:
Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture,Peshawar,Pakistan
5. Kanwal Lodhi:
Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture, Peshawar, Pakistan
Abstract:
Deep learning models have revolutionized the field of Computer Vision by offering advanced techniques for interpreting visual information. Throughout the past years deep learning approaches and applications have been displayed to beat past cutting edge machine learning methods in countless fields with computer vision being considered one of the conspicuous cases. The specified review paper gives a concise outline of Convolutional Neural Networks (CNNs), Deep Boltzmann Machines (DBMs) and Deep Belief Networks (DBNs), Autoencoders and Extreme Learning, the major deep learning methods exploited in computer vision issues. A brief record of their set of experiences, structures, benefits, and constraints is given, trailed by a depiction of their applications in different computer vision errands, object detection, face recognition, action, and activity recognition. Finally, a compact overview is given of future headings in designing deep learning schemes and techniques for the issues included in computer vision.
Page(s):
1-1
DOI:
DOI not available
Published:
Journal: Second International Conference on Computing Technologies, Tools and Applications (ICTAPP-24), June 4-6,2024 (Abstract Book), Volume: 0, Issue: 0, Year: 2024
Keywords:
Artificial Intelligence
,
Deep learning
,
Convolutional Neural Networks CNNs
,
Deep Belief Networks DBNs
,
Deep Boltzmann Machines DBMs
,
Autoencoders
References:
References are not available for this document.
Citations
Citations are not available for this document.