A notable increase in skin cancer mortality, one of the most lethal kinds of cancer, has been caused by a lack of awareness of warning signals and preventative measures. The need for early skin cancer diagnosis has in...
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This paper presents a high gain, compact size and dual band rectangular patch antenna for 5G applications. To enhance the gain of antenna, an equilateral triangle slots on the upper rectangular patch are constructed. ...
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Parkinson's disease (PD) is a neurological condition that results in a variety of motor and non-motor symptoms. It is caused due to degeneration of nerve cells in the central nervous system. The motor symptoms inc...
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With the advent of Reinforcement Learning(RL)and its continuous progress,state-of-the-art RL systems have come up for many challenging and real-world *** the scope of this area,various techniques are found in the *** ...
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With the advent of Reinforcement Learning(RL)and its continuous progress,state-of-the-art RL systems have come up for many challenging and real-world *** the scope of this area,various techniques are found in the *** such notable technique,Multiple Deep Q-Network(DQN)based RL systems use multiple DQN-based-entities,which learn together and communicate with each *** learning has to be distributed wisely among all entities in such a scheme and the inter-entity communication protocol has to be carefully *** more complex DQNs come to the fore,the overall complexity of these multi-entity systems has increased many folds leading to issues like difficulty in training,need for high resources,more training time,and difficulty in fine-tuning leading to performance *** a cue from the parallel processing found in the nature and its efficacy,we propose a lightweight ensemble based approach for solving the core RL *** uses multiple binary action DQNs having shared state and *** benefits of the proposed approach are overall simplicity,faster convergence and better performance compared to conventional DQN based *** approach can potentially be extended to any type of DQN by forming its *** extensive experimentation,promising results are obtained using the proposed ensemble approach on OpenAI Gym tasks,and Atari 2600 games as compared to recent *** proposed approach gives a stateof-the-art score of 500 on the Cartpole-v1 task,259.2 on the LunarLander-v2 task,and state-of-the-art results on four out of five Atari 2600 games.
Neural Networks are the state-of-the-art models that derive intelligent systems. Generalization of the neural network model is a judge of how well an architecture mimic human intelligence. Self-extraction neural netwo...
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Due to the complexity and urgency of information exchange in modern companies, optimizing communication protocols in the workplace is essential. Using methods from machine learning, this research takes a fresh tack to...
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This study addresses the formidable challenges encountered in automated brain tumor segmentation, including the complexities of irregular shapes, ambiguous boundaries, and intensity variations across MRI modalities. M...
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In Breast Cancer ML is instrumental in early detection through the analysis of mammographic and histopathological images, assessing individual risk factors, personalizing treatment plans based on genomic data, and pro...
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Discontinuity in long Deoxyribonucleic Acid (DNA) sequences creates harmful diseases. Changes in the DNA structure refers to changes in the human immunity system. Tuberculosis is a critical disease that causes coughin...
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The long sequence time-sequence forecasting problem attracts a lot of organizations. Many prediction application scenes are about long sequence time-sequence forecasting problems. Under such circumstances, many resear...
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