Multimedia Concepts on Object Detection and Recognition with F1 Car Simulation Using Convolutional Layers

Abstract

This paper presents a framework for detecting objects in images based on global features and contours. The first step is a shape matching algorithm that uses the background subtraction process. Object detection is accomplished by an examination of the oversegmentation of the image, where the space of the potential boundary of the object is examined to identify boundaries that have a direct resemblance to the prototype of the object type to be detected. Our analysis method removes edges using bilinear interpolation and reestablishes color sensors as lines and retracts background lines from the previous frame. Object contours are generated with clustered lines. The objects detected will then be recognized using the extraction technique. Here, we analyze the color and shape characteristics with which each object is capable of managing occlusion and interference. As an extension of object detection and recognition, F1 car simulation is experimented with simulation using various layers, such as layer drops, convolutionary layers, and boundary elimination, avoiding obstacles in different pathways.

Smart-Hydroponic-Based Framework for Saffron Cultivation: A Precision Smart Agriculture Perspective

“…The IoT protocols used for the data transfer within the network are CoAP (Constrained Application Protocol) and STOMP (Simple Text Oriented Messaging Protocol). CoAP and STOMP can be used for data transfer in different applications, such as smart healthcare and smart education, due to the security offered wirelessly using other technologies such as artificial intelligence and fuzzy logic [73][74][75][76][77][78][79][80][81][82][83][84][85][86].…”

Hybrid Optimized GRU-ECNN Models for Gait Recognition with Wearable IOT Devices

“…e data collected in the cloud are downloaded offline and data preprocessing steps are used for effective data separation and extraction. To achieve less computational complexity with high accuracy of segmentation, this paper uses the novel Pearson correlation sliding window technique [41], which combines the Pearson correlation coefficient [42] and Sliding Window techniques. e value of P plays an important role in the data extraction, in which different thresholds are used for effective data extraction over a period of time.…”

Harris Hawk Optimization: A Survey onVariants and Applications

“…Fiber wireless (FiWi) integrates wireless and optical networks. It can reduce complexity and cost by combining wireless and fiber networks, such as mobility of wireless networks and large bandwidth availability through optical networks [ 92 , 93 ]. To place multiple optical units at optimal locations in FiWi, Singh and Prakash [ 94 ] used the HHO algorithm.…”