Stock market’s volatile and complex nature makes it difficult to predict the market situation. Deep Learning is capable of simulating and analyzing complex patterns in unstructured data. Deep learning models have app...
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We propose to perform an image-based framework for electrical energy meter *** aim is to extract the image region that depicts the digits and then recognize them to record the consumed *** the readings of serial numbe...
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We propose to perform an image-based framework for electrical energy meter *** aim is to extract the image region that depicts the digits and then recognize them to record the consumed *** the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time ***,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by *** this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and *** image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image *** training and evaluation,the image dataset is annotated to produce the ground truth of all the ***,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the *** proves to be robust against the mentioned image variations compared with the traditional handcrafted *** proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.
Traffic signs, and navigation provide drivers with crucial information about speed limits, hazards and are essential for maintaining road safety. Detecting these signs and classifying in real-time plays a vital for au...
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In-context learning for large language models (LLMs) is employed to design a novel hybrid optimization framework for multi-robot task allocation. Results show that this approach can improve existing approaches, such a...
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The main reason for coming up with self-driving cars is to enhance the safety of cars on the road by improving and reducing the occurrence of traffic accidents. Self-driving cars rely on advanced systems known as Adva...
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Fish diseases are among the major limiting factors to increase global aquaculture production. They lead to increased fish mortality, low breeding and growth rates, and low meat quality. The success of aquaculture is h...
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Cooperative coevolution (CC) algorithms, based on the divide-and-conquer strategy, have emerged as the predominant approach to solving large-scale global optimization (LSGO) problems. The efficiency and accuracy of th...
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The existing 5G new radio (NR) numerology supports certain values of parameters like subcarrier spacing, symbol duration, and guard interval for vehicle-to-everything (V2X) communications. However, with ever evolving ...
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The aim of this paper is to analyze the implementation of intelligent lighting within the concept of smart energy based on the possibility of saving and efficient use of energy, which is largely based on non-renewable...
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This article suggests a method for diminishing the voltage unbalance in a three-phase five-level diode-clamped inverter (DCI) through the use of hexagonal hysteresis space vector modulation (HHSVM). Capacitor voltage ...
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This article suggests a method for diminishing the voltage unbalance in a three-phase five-level diode-clamped inverter (DCI) through the use of hexagonal hysteresis space vector modulation (HHSVM). Capacitor voltage balancing leads to enhanced system efficiency, reduced stress on components, enhanced performance, abridged electromagnetic interference, and reduced total harmonic distortion. The proposed modulation technique and its implementation are thoroughly examined in this study, along with modeling and experiment data that show how efficient the method is at lowering the capacitor voltage unbalance in the proposed five-level DCI. Capacitor voltage unbalance is reduced with the use of this HHSVM approach to 0.95%, which is a superior reduction compared to traditional PWM methods. The paper also discusses the advantages of the proposed method over other existing methods, making it a promising solution for practical applications in power electronics systems.
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