Objective: The purpose of this paper was to use Machine Learning (ML) techniques to extract facial features from images. Accurate face detection and recognition has long been a problem in computer vision. According to...
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Image inpainting has made great achievements recently, but it is often tough to generate a semantically consistent image when faced with large missing areas in complex scenes. To address semantic and structural alignm...
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Heads-up computing aims to provide synergistic digital assistance that minimally interferes with users' on-the-go daily activities. Currently, the input modalities of heads-up computing are mainly voice and finger...
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The Nong Han Chaloem Phrakiat Lotus Park is a tourist attraction and a source of learning regarding lotus ***,as a training area,it lacks appeal and learning motivation due to its conventional presentation of informat...
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The Nong Han Chaloem Phrakiat Lotus Park is a tourist attraction and a source of learning regarding lotus ***,as a training area,it lacks appeal and learning motivation due to its conventional presentation of information regarding lotus *** current study introduced the concept of smart learning in this setting to increase interest and motivation for *** neural networks(CNNs)were used for the classification of lotus plant species,for use in the development of a mobile application to display details about each *** scope of the study was to classify 11 species of lotus plants using the proposed CNN model based on different techniques(augmentation,dropout,and L2)and hyper parameters(dropout and epoch number).The expected outcome was to obtain a high-performance CNN model with reduced total parameters compared to using three different pre-trained CNN models(Inception V3,VGG16,and VGG19)as *** performance of the model was presented in terms of accuracy,F1-score,precision,and recall *** results showed that the CNN model with the augmentation,dropout,and L2 techniques at a dropout value of 0.4 and an epoch number of 30 provided the highest testing accuracy of *** best proposed model was more accurate than the pre-trained CNN models,especially compared to Inception *** addition,the number of total parameters was reduced by approximately 1.80–2.19 *** findings demonstrated that the proposed model with a small number of total parameters had a satisfactory degree of classification accuracy.
In this paper, we delve into the transformative landscape of education amidst the disruptive advances of generative AI (GenAI), characterized by an unprecedented capacity to generate new information with tools such as...
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Agriculture is the major source of food and significantly contributes to Indian employment, and the economy is intricately tied to the outcomes of crop management, where the final yield and market prices play crucial ...
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Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things(IoT)*** the emergence of IoT...
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Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things(IoT)*** the emergence of IoT-based services,the industry of internet-based devices has *** number of these devices has raised from millions to billions,and it is expected to increase further in the near ***,additional challenges will be added to the traditional centralized cloud-based architecture as it will not be able to handle that growth and to support all connected devices in real-time without affecting the user *** data aggregation models for Fog enabled IoT environ-ments possess high computational complexity and communication ***-fore,in order to resolve the issues and improve the lifetime of the network,this study develops an effective hierarchical data aggregation with chaotic barnacles mating optimizer(HDAG-CBMO)*** HDAG-CBMO technique derives afitness function from many relational matrices,like residual energy,average distance to neighbors,and centroid degree of target ***,a chaotic theory based population initialization technique is derived for the optimal initial position of ***,a learning based data offloading method has been developed for reducing the response time to IoT user requests.A wide range of simulation analyses demonstrated that the HDAG-CBMO technique has resulted in balanced energy utilization and prolonged lifetime of the Fog assisted IoT networks.
A XGBoost-Based System in Cervical type cancer Diagnostics are proposed in the current research work. Generally Cervical type of cancer will be a significant health concern worldwide, particularly in the regions with ...
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The Computational Visual Media(CVM)conference series is intended to provide a prominent international forum for exchanging innovative research ideas and significant computational methodologies that either underpin or ...
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The Computational Visual Media(CVM)conference series is intended to provide a prominent international forum for exchanging innovative research ideas and significant computational methodologies that either underpin or apply visual media.
Hypertension, also referred to as high blood pressure, is a condition arising from the consistently high blood pressure against artery walls. The volume and output of blood from the heart primarily control blood press...
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