Community detection is a valuable tool for studying the function and dynamic structure of most real-world networks. Existing techniques either concentrate on the network's topological structure or node properties ...
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Deep learning is the subset of artificial intelligence and it is used for effective decision *** Sensor based automated irrigation system is proposed to monitor and cultivate *** system consists of Distributed wire-les...
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Deep learning is the subset of artificial intelligence and it is used for effective decision *** Sensor based automated irrigation system is proposed to monitor and cultivate *** system consists of Distributed wire-less sensor environment to handle the moisture of the soil and temperature *** is automated process and useful for minimizing the usage of resources such as water level,quality of the soil,fertilizer values and controlling the whole *** mobile app based smart control system is designed using deep belief *** system has multiple sensors placed in agriculturalfield and collect the *** collected transmitted to cloud server and deep learning process is applied for making *** residue analysis method is proposed for analyzing auto-mated and sensor captured ***,we used 512×512×3 layers deep belief network and 10000 trained data and 2500 test data are taken for *** is automated process once data is collected deep belief network is *** performance is compared with existing results and our process method has 94%of accuracy ***,our system has low cost and energy consumption also suitable for all kind of agriculturalfields.
The Internet of Things (IoT), which enables seamless connectivity and effective data exchange between physical items and digital systems, has completely changed the way we interact with our surroundings. This study ev...
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Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by...
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Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology. Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets, thereby presenting a breakthrough in utilizing wearable sensors for practical applications. Beyond traditional machine-learning techniques for classifying simple gestures, advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets. Machine-learning techniques have improved the ability to perceive, and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition, providing real-time feedback to users. This forms a crucial component of future wearable electronics, contributing to a robust human–machine interface. In this review, we provide a comprehensive summary covering materials, structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.
Introduction: Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) both have their areas of specialty in the medical imaging world. MRI is considered to be a safer modality as it exploits the magnetic propert...
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Capacitive pressure sensors have attracted considerable interest due to their high sensitivity, low energy consumption, and potential for miniaturization, making them suitable for applications in automotive systems, c...
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The concept of a medical intelligent system has steadily garnered attention as modern technology advances. An intelligent medical system is a medical system that develops a certain amount of intelligence and performs ...
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The integration of machine learning (ML) and Internet of Things (IoT) technologies has a scope of improvement in precision farming techniques and revolutionise the agriculture sector. This research paper examines the ...
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Anomaly detection is a method of categorizing unexpected data points or events in a dataset. Variational Auto-Encoders (VAEs) have proved to handle complex problems in a variety of disciplines. We propose a technique ...
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Now a day's tourism industry in Asia is more than ever being modernized by innovative technologies, an undisputable reality that was converting the sector in different ways. To create a memorable experience there ...
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