The Internet of Things (IoT) has revolutionized the way data is handled and collected, allowing for large amounts of information to be revolutionized quickly and efficiently. This has paved the way for Machine Learnin...
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One of the most active subfields of computer vision and pattern recognition, human action recognition seeks to identify specific actions in still photos. The wide range of possible uses in this area has attracted a lo...
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In recent years, there has been a remarkable increase in the use of machine learning (ML) technologies in healthcare settings. Despite this growth, a significant challenge persists: numerous promising initiatives rema...
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The quality of teaching and learning process can be improved through innovative methods like use of virtual reality. We introduce EnVision, a groundbreaking Virtual Reality based approach to revolutionize Artificial I...
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Multilingual speaker identification and verification is a challenging task, especially for languages with diverse acoustic and linguistic features such as Indo-Aryan and Dravidian languages. Previous models have strug...
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The accurate identification and segmentation of brain tumors using the medical imaging of the data is crucial for patient treatment planning. This study will look into advanced deep learning techniques, including Resi...
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Wireless Sensor Networks (WSNs) have advanced quickly due to the fast expansion of wireless networks. Yet, because of their ease of use and versatility, security concerns have grown. This means that conducting researc...
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ISBN:
(纸本)9798350348460
Wireless Sensor Networks (WSNs) have advanced quickly due to the fast expansion of wireless networks. Yet, because of their ease of use and versatility, security concerns have grown. This means that conducting research on intrusion protection in WSNs is now essential. Denial of Service (DoS) assaults are among the most common types of network attacks. They are dangerous because they take down the target network in order to accomplish their goal. Within WSNs, where devices function with limited resources, a denial-of-service attack has the potential to be disastrous. This research suggests a novel solution for WSNs, which are susceptible to assaults because to their devices' little storage capacity. To find abnormalities in DoS traffic within WSNs, the technique combines a Deep Convolutional Neural Network (DCNN) with Principal Component Analysis (PCA). By detecting and reducing the effects of DoS assaults, and by utilising the complementary capabilities of PCA and DCNN in this particular situation, the goal is to improve the security of WSNs. Compared with other traditional DL architectures, the proposed model has a more simplified structure and better feature extraction capabilities. This special combination gives it the power to quickly identify anomalous network activity in WSNs devices, especially those with limited storage. Because of its lightweight design, the suggested model addresses the inherent resource limits and guarantees optimal performance in the context of WSNs. A variety of assessment measures, such as confusion matrices, different classification metrics, and Receiver Operating Characteristic (ROC) curves, are used to verify the effectiveness of the suggested model. These metrics are used to evaluate the model's categorization performance in a rigorous manner. Extensive experimental comparisons reveal that the small size of the proposed model outperforms other popular models for anomalous traffic detection with regards to classification performance
The agriculture sector plays a significant role as it not only serves in meeting a substantial portion of worldwide food requirements but is also servers as one of the key contributors to the country's economy. Ho...
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In computer vision and pattern recognition, image-based human activity detection has gained popularity as a research topic. The process of recognizing human behavior from an image is called activity recognition. Here,...
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When experiencing dry eyes or fatigue, using eye drops can provide relief. However, some people are not good at applying eye drops. This study proposes a system that automatically applies eye drops while playing a gam...
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