0% Complete
Home
/
11th International Conference on Computer and Knowledge Engineering
Efficient Object Detection using Deep Reinforcement Learning and Capsule Networks
Authors :
Sobhan Siamak
1
Eghbal Mansoori
2
1- Department of Computer Science and Engineering and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
2- Department of Computer Science and Engineering and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
Keywords :
Deep Reinforcement Learning, Capsule Networks, Object Detection, Computer Vision
Abstract :
Recently, with the advent of deep learning, significant advances in computer vision have been made. One of the traditional and important tasks in computer vision is object detection. Object detection methods based on pre-defined anchors or region proposal suffer from high computational complexity. We propose a new method based on deep reinforcement learning and capsule networks for object detection in images. Capsules are a group of neurons that communicate with each other in the form of routing. The main idea is to use capsule networks as the heart of deep reinforcement learning and train an intelligent agent for a more accurate search of objects and localize them in the image. We also defined a new function called CEU and used it as part of the movement reward function. We evaluated our method on two well-known object detection benchmark datasets called PASCAL Visual Object Classes (VOC) 2007, and 2012. Experiments illustrate that the proposed method achieved higher precision than similar methods in terms of not being a region proposal.
Papers List
List of archived papers
Non-Negative Matrix Factorization improves Residual Neural Networks
Hojjat Moayed
Optimal PMU Placement Considering Reliability of Measurement System in Smart Grids
Mohammad Shahraeini - Shahla Khormali - Ahad Alvandi
IranITJobs2021: a Dataset for Analyzing Iranian Online IT Job Advertisements Collected Using a New Crowdsourcing Process
Fakhroddin Noorbehbahani - Nikta Akbarpour - Mohammad Reza Saeidi
Dynamic Knowledge Enhanced Neural Fashion Trend Forecasting with Quantile Loss
Fatemeh Rooholamini - Reza Azmi - Mobina Khademhossein - Maral Zarvani
A Survey on Semi-Automated and Automated Approaches for Video Annotation
Samin Zare - Mehran Yazdi
Intensity-Image Reconstruction Using Event Camera Data by Changing in LSTM Update
Arezoo Rahmati Soltangholi - Ahad Harati - Abedin Vahedian
A New Hypercube Variant: Pruned Shuffle Connected Cube
Reza Latifi - Mahmoud Naghibzadeh
FGM Copula based Analysis of Coverage Region for Wireless Three-User Multiple Access Channel with Correlated Channel Coefficients
Mona Sadat Mohsenzadeh - Ghosheh Abed Hodtani
Prediction of West Texas Intermediate Crude-oil Price Using Hybrid Attention-based Deep Neural Networks: A Comparative Study
Alireza Jahandoost - Mahboobeh Houshmand - Seyyed Abed Hosseini
Standardized ReACT Logits: An Effective Approach for Anomaly Segmentation in Self-driving Cars
Mahdi Farhadi - Seyede Mahya Hazavei - Shahriar Baradaran Shokouhi
more
Samin Hamayesh - Version 41.3.1