Object Detection using Machine Learning and Deep Learning
Keywords:
Object Detection, Convolutional Neural Network, Deep Learning, Machine LearningAbstract
With the increasing automation in today’s world, the need for finding and labelling objects in images and videos has grown exponentially. Be it managing traffic, self-driving cars or medical imaging, object detection is being used everywhere around us. Traditional methods for object detection, like SIFT or HOG features, are efficient but no longer compatible for today's needs as the processing of images needed are in real time that can not be done by these methods. These methods also make the procedure of training and preparing our model really complex and can only work with well-lit, front-faced, full-picture images of objects which is not always possible to achieve. So, the deep learning methods for object detection, like R-CNN, YOLO or RetinaNet, were introduced.These methods are being used worldwide to detect objects and make object detection automated and simpler. In this paper, we provide a review on both machine learning and deep learning approaches for object detection. Our review begins with an introduction to object detection, then we focus on all the methods used for object detection - machine learning approach and deep learning approach. Then we move on to all the advantages, challenges and applications of object detection. To conclude it, we mentioned the future scopes everyone can look forward to.
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Mukesh Tiwari, Dr. Rakesh Singhai’s “A review of detection and tracking of object from image and video sequences” in International Journal of Computational Intelligence Research ISSN 0973-1873 Volume 13, Number 5 (2017), pp. 745-765
An Hybrid and Synthetic Machine Translation Model for English to Ahirani Language IJGDC 2005-4262, 2021
Abdul Vahab, Maruti S Naik, Prasanna G Raikar, Prasad S R’s “Applications of Object Detection System” in International Research Journal of Engineering and Technology (IRJET) in Volume: 06, Issue: 04 | Apr 2019
Weather Prediction Machine Learning GIS 1869-9391 2021
Machine Learning for Weather Forcasting using Freely Available Weather Data in Python GIS 1869-9391 2021
Cloud Computing and security Fundamentals IJCSMC 2320-088X April 2022
Python For Web Developement IJCSMC 2320-088X April 2022
Sreelekshmi K J, Therese Yamuna Mahesh’s “Human Identification Based on the Histogram of Oriented Gradients” in International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 3 Issue 7, July – 2014
Big Data Analytics:Research Issues and Challenges GIS 1869-9391 May 2022
Application based Research Study On Learning Personalization with Artifical Nural Networks IJRAR 2349-5138 June 2022
Seizure And Sleeping Disorder Detection From Eeg Using Machine Learning JPSET 2229-7111 March 2022
Jifeng Dai, Haozi Qi, Yuven Xiong, Yi Li, Guodong Zhang, Han Hu, Yichen Wei’s “Deformable Convolutional Networks” in Microsoft Research Asia
The Single Injection Current Flow An Insulator Containing Distributed Deep Traps Around An Energy Operating Under High Field Regime Neuroquantology 1303-5150 Nov 2022
Face Detection using Machine Leaning JOEL 1005-0086 Nov 2022
Noise Temperature In Single Injection Cylindrical Current Flow In Insulator At Low And High Injection Level Of Current. Journal of Data Acquisition and Processing 2368-7487 Mar-23
Jun Deng’s “A review of research on object detection based on deep learning” in Journal of Physics: Conference Series
A neural network based machine translation model for english to ahirani language Journal of Data Acquisition and Processing 1004-9037 Jan-23
A web page classification survey on techniques using text Advances in Water Science 1004-9037 Jan-23
Accidents Sensing Car Wiper and Location using IoT Based Notific Advances in Water Science 1001-6791 Jan-23
Manjula S., Lakshmi Krishnamurthy’s “A Study on Object Detection” in International Journal of Pharmacy and Technology
Intelligent Face Detection using Machine Leaning Advances in Water Science 1001-6791 Jan-23
Crime Rate Prediction using Cyber Security and Artificial Intelligent European Chemical Bulletin 1001-6791 Jan-23
Recognition of Vehicle number Plate for collection of toll European Chemical Bulletin 2063-5346 May-23
B. Alexe, T. Deselaers, V. Ferrari, “Measuring the objectness of image windows” in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2012
Design of an ROV to find Dead Bodies Underwater Journal of Data Acquisition and Processing 2063-5346 May-23
Literature Survey on OSOID International Journal of Research Publication and Reviews 2582-7421 May 23
C. Szegedy, S. Reed, D. Erhan, D. Anguelov’s “Scalable, high-quality object detection,” in arXiv:1412.1441 (v1), 2015
Y. Zhu, R. Urtasun, R. Salakhutdinov, S. Fidler’s “segdeepm: Exploiting segmentation and context in deep neural networks for object detection” in CVPR, 2015
Using Yolo V7 Development Of Complete Vids Solution Based On Latest Requirements To Provide Highway Traffic And Incident Real Time Info To The Atms Control Room Using Artificial Intelligence Journal of Survey in Fisheries Sciences ISSN-2368-7487 27-Jun-23
Intrusion Detection in the Digital Age: A Hybrid Data Optimization Perspective International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING ISSN:2147-679921 29-Jun-23
K. K. Sung, T. Poggio’s “Example-based learning for view-based human face detection” in IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 1, pp. 39–51, 2002
Gooda, S. K. ., Chinthamu, N. ., Selvan, S. T. ., Rajakumareswaran, V. ., & Paramasivam, G. B. . (2023). Automatic Detection of Road Cracks using EfficientNet with Residual U-Net-based Segmentation and YOLOv5-based Detection. International Journal on Recent and Innovation Trends in Computing and Communication, 11(4s), 84–91. https://doi.org/10.17762/ijritcc.v11i4s.6310
Sánchez, F., Đorđević, S., Georgiev, I., Jacobs, M., & Rosenberg, D. Exploring Generative Adversarial Networks for Image Generation. Kuwait Journal of Machine Learning, 1(4). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/147
Raghavendra, S., Dhabliya, D., Mondal, D., Omarov, B., Sankaran, K.S., Dhablia, A., Chaudhury, S., Shabaz, M. Retracted: Development of intrusion detection system using machine learning for the analytics of Internet of Things enabled enterprises (2023) IET Communications, 17 (13), pp. 1619-1625.
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