The susceptibility of digital image communication is a crucial issue in the domain of digital transfer. The image encryption literature has presented numerous cryptosystems to enhance communication security. Image enc...
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The paper explores the use of deep learning models for accurate head and neck tumor segmentation, aiming to improve efficiency and accuracy in medical imaging. The main focus is to employ evolutionary algorithms to op...
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This study developed a modern autonomous navigation system using proximity and accelerometer sensors, along with deep reinforcement learning algorithms. The system ensures safety by providing real-time data on obstacl...
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Efficient Real-Time Face recognition-based attendance systems with deep learning algorithms strive for precise and real-time performance in managing attendance across various institutions. This solution outlines key t...
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In this work, we address the strategic placement and optimal sizing of electric vehicle charging stations for cities as well as highway traffic to minimize overall cost. We formulate the problem as a Mixed Integer Lin...
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This research investigates the use of reinforcement learning (RL) algorithms for optimal control systems in electrical engineering. The article discusses four popular RL algorithms - Q-learning, Deep Q Network (DQN), ...
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The global demand for electrical energy has witnessed a substantial increase, presenting a challenge for power systems worldwide. In addition to technical considerations, the escalating issue of global warming has bec...
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In this work, a frequency reconfigurable wearable antenna incorporating a varactor diode is proposed. The antenna is designed using a Felt substrate, chosen for its lightweight, flexible, and low-loss properties, maki...
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As China's social economy progresses, the amount of equipment in distribution networks continues to grow, leading to increasingly complex system operations. In this environment, traditional centralized control met...
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This paper explores the importance of activation functions in enhancing the performance of intrusion detection systems (IDSs) using deep learning. Traditional activation functions such as ReLU, Sigmoid, and Tanh face ...
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