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A Robust Object Detection and Recognition using Deep Features based Appearance-Model
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 180 - Number 24 |
| Year of Publication: 2018 |
| Authors: Ranjana Kapila, Heena Wadhwa |
10.5120/ijca2018916572
|
Ranjana Kapila, Heena Wadhwa . A Robust Object Detection and Recognition using Deep Features based Appearance-Model. International Journal of Computer Applications. 180, 24 ( Mar 2018), 29-31. DOI=10.5120/ijca2018916572
Abstract
The object detection models are very important parts of the vehicular monitoring, traffic surveillance or traffic planning in the urban or crowded areas of the cities. The satellites images are the primary sources of the urban surveillance; hence the proposed model has been proposed to work with the satellite imagery data. The object detection and localization plays the vital role in the various surveillance applications, vision based applications, augmented reality and robotics. The object detection and recognition becomes very important to localize the specific objects for augmented reality and robotics applications. In this thesis, the work would be carried forward on the mechanism using the Deep Features based Appearance-Model for the object detection and recognition in the target images.
References
- Plebe A, Grasso G. Localization of spherical fruits for robotic harvesting. Mach Vis Appl. 2001;13(2):70-79. doi:10.1007/PL00013271
- Fleites FC, Wang H, Chen SC. Enhancing Product Detection with Multicue Optimization for TV Shopping Applications. IEEE Trans Emerg Top Comput. 2015;3(2):161-171.
- Zhang B, Huang W, Wang C, et al. Computer vision recognition of stem and calyx in apples using near-infrared linear-array structured light and 3D reconstruction. Biosyst Eng. 2015;139(November 2015):25-34.
- Alfatni MSM, Shariff ARM, Shafri HZM, Saaed OM Ben, Eshanta OM. Oil palm fruit bunch grading system using red, green and blue digital number. J Appl Sci. 2008;8(8):1444-1452.
- Pouladzadeh P, Villalobos G, Almaghrabi R, Shirmohammadi S. 2012 IEEE International Conference on Multimedia and Expo Workshops A Novel SVM Based Food Recognition Method for Calorie Measurement Applications. 2012:495-498.
- Ishak W, Ismail W. Hue Optical Properties to Model Oil Palm Fresh Fruit Bunches Maturity Index. :15-17.
- Noorul S, Hassan A, Nadiah N, Abdul S, Zaw Z, Win SL. VISION BASED E NTOMOLOGY– HOW TO EFFECTIVELY EXPLOIT COLOR AND S HAPE. 2014;4(2):1-12.
- Bama BS. CONTENT BASED LEAF IMAGE RETRIEVAL ( CBLIR ) USING SHAPE , COLOR AND TEXTURE FEATURES. 2011;2(2):202-211.
- Jiménez, A. R., Ceres, R., & Pons, J. L. (2000). A vision system based on a laser range-finder applied to robotic fruit harvesting. Machine Vision and Applications, 11(6), 321-329.
- Agriculture F, Haji H, Universiti R, et al. Image based modeling for oil palm fruit maturity prediction. 2015;(April 2010).
- Margaritis D, Thrun S. Learning To Locate An Object in 3D Space From A Sequence Of Camera Images. 1998:332–340.
- Girshick R, Donahue J, Member S, Darrell T, Malik J. Region-based Convolutional Networks for Accurate Object Detection and Segmentation. :1-16.
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