Automatic lane detection is a classical task in autonomous vehicles that traditional computer vision techniques can perform. However, such techniques lack reliability for achieving high accuracy while maintaining adequate time complexity in the context of real-time detection in complex and dynamic road scenes. Deep neural networks have proved their ability to achieve competing accuracy and time

Recent years witness a great deal of interest in artificial intelligence (AI) tools in the area of optimization. AI has developed a large number of tools to solve the most difficult search-and-optimization problems in computer science and operations research. Indeed, metaheuristic-based algorithms are a sub-field of AI. This study presents the use of the metaheuristic algorithm, that is, water

Real parameter optimization is one of the active research fields during the last decade. The performance of LSHADE-SPACMA was competitive in IEEE CEC’2017 competition on Single Objective Bound Constrained Real-Parameter Single Objective Optimization. Besides, it was ranked fourth among twelve papers were presented on and compared to this new benchmark problems. In this work, an improved version

Unmanned aerial vehicles (UAVs) are used for a wide range of applications, including wireless communication systems, which have the potential to provide cost-effective wireless connectivity for a wide variety of applications. The present UAV models lack the flexibility needed to carry the mission's varied payloads. As a result, appropriate design and analysis of the UAV structure are essential

Mobile edge computing (MEC) is a key enabling technology for supporting high-speed and low latency services in the fifth generation (5G) and beyond networks. MEC paradigm moves computational resources from centralized cloud servers towards the edge of the network, nearer to the users. However, edge computation resources increase the power consumption of the network. Moreover, the non-uniform

The increase in population, food demand, and the pollution levels of the environment are considered major problems of this era. For these reasons, the traditional ways of farming are no longer suitable for early and accurate detection of biotic stress. Recently, precision agriculture has been extensively used as a potential solution for the aforementioned problems using high resolution optical

Random numbers play an essential role in guaranteeing secrecy in most cryptographic systems. A chaotic optical signal is exploited to achieve high-speed random numbers. It could be generated by using one or more semiconductor lasers with external optical feedback. However, this system faces two major issues, high peak to average power ratio (PAPR) and parameter variations. These issues highly

Face shape classification is considered one of the trending topics in the artificial intelligence research field. Face shape classification can be employed in many broad-scoped projects, such as hairstyle recommendation systems in the beauty and fashion industry. In this paper, the inception v3 model was employed to reach the highest possible performance for classifying the different face shapes

In the past few decades, a lot of optimization methods have been applied in estimating the parameter of photovoltaic (PV) models and obtained better results, but these methods still have some deficiencies, such as higher time complexity and poor stability. To tackle these problems, an enhanced success history adaptive DE with greedy mutation strategy (EBLSHADE) is employed to optimize parameters

Traffic offloading is considered a promising solution to relieve the explosive congestion of future cellular networks. Existing works in the literature focus on increasing the number of offloaded users. Nevertheless, users' traffic load plays a critical role in having the ability to relay the data intended for the cellular users. In this paper, we consider the traffic offloading problem in a