Object Recognition and Detection in Remote Sensing Images: A Comparative Study

In this paper, we have provided a brief literature survey of object recognition & detection in remote sensing. These scene recognition images have more components and more challenging issues in the range of aerial image resolutions. It also shows a critical act as a limited area based on functions. The object detection in optical remote sensing has the best critical part of over supposing conditions of characteristic against affecting a model inputs. Certain moving characteristic act as a set of quality to define a based on personal action. This paper provides a brief summary of different object detection in remote sensing images and also discuss about their strength and limitation. The main focus of this review paper is on the satellite image. A subsists in patent of scene recognition of current model act on a freshly process. Inter relates to the land uses analysis system, other model analysis process as well as turn to the appropriate function. We have also discussed the problems and advancement of current scenario and give three research directions for deep learning for medical image recognition, image classification, and health care. We ensure this review article will provide adequate directions and scope for the betterment of the research community in the field of object recognition & detection in remote sensing.

[1]  Ashwani Kumar,et al.  Design of Secure Image Fusion Technique Using Cloud for Privacy-Preserving and Copyright Protection , 2019, Int. J. Cloud Appl. Comput..

[2]  Shuicheng Yan,et al.  Scale-Aware Fast R-CNN for Pedestrian Detection , 2015, IEEE Transactions on Multimedia.

[3]  Ross B. Girshick,et al.  Fast R-CNN , 2015, 1504.08083.

[4]  Nuno Vasconcelos,et al.  Learning Complexity-Aware Cascades for Deep Pedestrian Detection , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[5]  Kenji Sugawara,et al.  Scene Recognition Method by Bag of Objects Based on Object Detector , 2018, 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS).

[6]  S. P. Ghrera,et al.  An ID-based Secure and Flexible Buyer-seller Watermarking Protocol for Copyright Protection , 2017 .

[7]  Pierre Alliez,et al.  Convolutional Neural Networks for Large-Scale Remote-Sensing Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Junwei Han,et al.  A Survey on Object Detection in Optical Remote Sensing Images , 2016, ArXiv.

[9]  Rogério Schmidt Feris,et al.  A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection , 2016, ECCV.

[10]  Pietro Perona,et al.  A Bayesian hierarchical model for learning natural scene categories , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[11]  Ashwani Kumar,et al.  A lightweight buyer-seller watermarking protocol based on time-stamping and composite signal representation , 2018 .

[12]  Cordelia Schmid,et al.  Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[13]  Ashwani Kumar,et al.  A Review on Implementation of Digital Image Watermarking Techniques Using LSB and DWT , 2019, Information and Communication Technology for Sustainable Development.

[14]  S. P. Ghrera,et al.  Implementation of Wavelet Based Modified Buyer-Seller Watermarking Protocol ( BSWP ) , 2014 .

[15]  Jungwon Lee,et al.  Fused DNN: A Deep Neural Network Fusion Approach to Fast and Robust Pedestrian Detection , 2016, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV).

[16]  Ashwani Kumar,et al.  RSA Using Montgomery Powering Ladder on Dual Core , 2020 .

[17]  Huimin Ma,et al.  3D Object Proposals for Accurate Object Class Detection , 2015, NIPS.

[18]  Ali Farhadi,et al.  YOLO9000: Better, Faster, Stronger , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Andrea Vedaldi,et al.  Weakly Supervised Deep Detection Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Ashwani Kumar,et al.  Digital Image Forgery Detection Techniques: A Comprehensive Review , 2019, 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA).

[21]  Kaiming He,et al.  Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Ashwani Kumar,et al.  Modified Buyer Seller Watermarking Protocol based on Discrete Wavelet Transform and Principal Component Analysis , 2016 .