ISSN 2394-5125
 

Research Article 


REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING

Sushant Joshi1, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare.

Abstract
Computer vision is a field of deep learning that makes use of webcam from which real time object detection and identification is done via image processing. It is used to detect various objects, human beings, animals. There is a remarkable need for a lightweight model for multiple object detection for devices which are not capable of computational power like laptops and mobile phones. This paper proposed a model for live multiple object detection based on CNN called as Single time Multiple Detection (STD) which is a lightweight model used in proposed work. Keras is a powerful tool that is used for training the model and quickly enabled to build and deploy as an image recognition software. This paper mostly focuses on detecting multiple objects in single time to ease multiple object detection, we have got keras used to train models and we have used CNN algorithms for implementation. This model is experimented on coco dataset for detecting single time multiple objects. Experimental results reveal that use of STD models increases the accuracy level in identifying the real time multiple objects.

Key words: Multiple Object Detection, Computer Vision, CNN, Deep Learning, Image Processing, TensorFlow, keras.


 
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How to Cite this Article
Pubmed Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare. REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING. JCR. 2020; 7(19): 1074-1081. doi:10.31838/jcr.07.19.133


Web Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare. REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING. http://www.jcreview.com/?mno=104057 [Access: July 17, 2020]. doi:10.31838/jcr.07.19.133


AMA (American Medical Association) Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare. REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING. JCR. 2020; 7(19): 1074-1081. doi:10.31838/jcr.07.19.133



Vancouver/ICMJE Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare. REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING. JCR. (2020), [cited July 17, 2020]; 7(19): 1074-1081. doi:10.31838/jcr.07.19.133



Harvard Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare (2020) REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING. JCR, 7 (19), 1074-1081. doi:10.31838/jcr.07.19.133



Turabian Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare. 2020. REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING. Journal of Critical Reviews, 7 (19), 1074-1081. doi:10.31838/jcr.07.19.133



Chicago Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare. "REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING." Journal of Critical Reviews 7 (2020), 1074-1081. doi:10.31838/jcr.07.19.133



MLA (The Modern Language Association) Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare. "REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING." Journal of Critical Reviews 7.19 (2020), 1074-1081. Print. doi:10.31838/jcr.07.19.133



APA (American Psychological Association) Style

Sushant Joshi, AlkaLondhe, Abhishek Ratnaparkhi, Rhushikesh Valiv, Rohit Shingare (2020) REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING. Journal of Critical Reviews, 7 (19), 1074-1081. doi:10.31838/jcr.07.19.133





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