CLASSIFYING WEATHER BASED VISUAL DATA USING NOVEL HYBRID APPROACH
Rachit Agarwal , Aarsh Sapra, Sasi Rekha Sankar
Student, SRM Institute of Science and Technology
Aspects such as the climate play a significant part in the expansion of businesses in the current period, in which companies from a variety of sectors are collaborating to fulfil the objectives of commercial enterprises. The climate not only has an impact on our day-to-day lives, but it also plays a significant role in a wide range of businesses, including retail, construction, and supply chain management, among others. Aside from that, it also has an effect on the functionality of a great deal of visual systems, such as those used in vehicles to assist drivers, outdoor video observation system, and so on. The presence of fog in the weather poses a significant risk for automobile accidents. The impact of the severe weather that has been affecting the region can also be observed in India. Although there is a significant amount of study that is now being conducted in the topic of "Weather Analytics," there is still a significant amount of research that needs to follow the role of A.I. in this particular field. This research work presents a specific study that has been done to fill the void. The aim of this research is to investigate potential applications of combining various deep learning models known as convolutional neural networks for solving weather detection issues. Expensive sensors are required for the more conventional methods of determining the current state of the weather. This article provides a strategy using computer vision to detect real weather conditions with precise accuracy in order to keep the costs to a minimum.
Keywords: Computer Vision, Weather Classification, Image processing, Deep Learning, Ensemble Learning, Accuracy
Journal Name :
EPRA International Journal of Research & Development (IJRD)
Published on : 2022-11-18