%0 Journal Article %1 noauthororeditor %A Vinod, P. Rajeshwari | P. Abhishek | P. Srikanth | T. %D 2019 %J International Journal of Trend in Scientific Research and Development %K Artificial Intelligence and computer deep detection learning networks. neural object vision %N 3 %P 1663-1665 %R https://doi.org/10.31142/ijtsrd23422 %T Object Detection An Overview %U https://www.ijtsrd.com/computer-science/artificial-intelligence/23422/object-detection-an-overview/p-rajeshwari %V 3 %X The goal of the project is to run an object detection algorithm on every frame of a video, thus allowing the algorithm to detect all the objects in it, including but not limited to people, vehicles, animals etc. Object recognition and detection play a crucial role in computer vision and automated driving systems. We aim to design a system that does not compromise on performance or accuracy and provides real time solutions. With the importance of computer vision growing with each passing day, models that deliver high performance results are all the more dominant. Exponential growth in computing power as well as growing popularity in deep learning led to a stark increase in high performance algorithms that solve real world problems. Our model can be taken a step further, allowing the user the flexibility to detect only the objects that are needed at the moment despite being trained on a larger dataset. P. Rajeshwari | P. Abhishek | P. Srikanth | T. Vinod Öbject Detection: An Overview" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23422.pdf

@article{noauthororeditor, abstract = {The goal of the project is to run an object detection algorithm on every frame of a video, thus allowing the algorithm to detect all the objects in it, including but not limited to people, vehicles, animals etc. Object recognition and detection play a crucial role in computer vision and automated driving systems. We aim to design a system that does not compromise on performance or accuracy and provides real time solutions. With the importance of computer vision growing with each passing day, models that deliver high performance results are all the more dominant. Exponential growth in computing power as well as growing popularity in deep learning led to a stark increase in high performance algorithms that solve real world problems. Our model can be taken a step further, allowing the user the flexibility to detect only the objects that are needed at the moment despite being trained on a larger dataset. P. Rajeshwari | P. Abhishek | P. Srikanth | T. Vinod "Object Detection: An Overview" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23422.pdf }, added-at = {2019-06-06T10:28:54.000+0200}, author = {Vinod, P. Rajeshwari | P. Abhishek | P. Srikanth | T.}, biburl = {https://www.bibsonomy.org/bibtex/226437fa399ecfa823092f0f3c00be099/ijtsrd}, doi = {https://doi.org/10.31142/ijtsrd23422}, interhash = {8b2b927d47f43f5d8acf04d91b06f98e}, intrahash = {26437fa399ecfa823092f0f3c00be099}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Artificial Intelligence and computer deep detection learning networks. neural object vision}, language = {English}, month = {March}, number = 3, pages = {1663-1665}, timestamp = {2019-06-06T10:28:54.000+0200}, title = {Object Detection An Overview }, url = {https://www.ijtsrd.com/computer-science/artificial-intelligence/23422/object-detection-an-overview/p-rajeshwari}, volume = 3, year = 2019 }