Multi-level sentence simplification generates simplified sentences with varying language proficiency levels. We propose Label Confidence Weighted Learning (LCWL), a novel approach that incorporates a label confidence ...
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Object detection plays a vital role in the video surveillance *** enhance security,surveillance cameras are now installed in public areas such as traffic signals,roadways,retail malls,train stations,and ***,monitor-ing...
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Object detection plays a vital role in the video surveillance *** enhance security,surveillance cameras are now installed in public areas such as traffic signals,roadways,retail malls,train stations,and ***,monitor-ing the video continually at a quicker pace is a challenging *** a consequence,security cameras are useless and need human *** primary difficulty with video surveillance is identifying abnormalities such as thefts,accidents,crimes,or other unlawful *** anomalous action does not occur at a high-er rate than usual *** detect the object in a video,first we analyze the images pixel by *** digital image processing,segmentation is the process of segregating the individual image parts into *** performance of segmenta-tion is affected by irregular illumination and/or low *** factors highly affect the real-time object detection process in the video surveillance *** this paper,a modified ResNet model(M-Resnet)is proposed to enhance the image which is affected by insufficient *** results provide the comparison of existing method output and modification architecture of the ResNet model shows the considerable amount improvement in detection objects in the video *** proposed model shows better results in the metrics like preci-sion,recall,pixel accuracy,etc.,andfinds a reasonable improvement in the object detection.
Globally,educational institutions have reported a dramatic shift to online learning in an effort to contain the COVID-19 *** fundamental concern has been the continuance of *** a result,several novel solutions have be...
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Globally,educational institutions have reported a dramatic shift to online learning in an effort to contain the COVID-19 *** fundamental concern has been the continuance of *** a result,several novel solutions have been developed to address technical and pedagogical ***,these were not the only difficulties that students *** implemented solutions involved the operation of the educational process with less regard for students’changing circumstances,which obliged them to study from *** should be asked to provide a full list of their *** a result,student reflections,including those from Saudi Arabia,have been analysed to identify obstacles encountered during the COVID-19 ***,most of the analyses relied on closed-ended questions,which limited student *** delve into students’responses,this study used open-ended questions,a qualitative method(content analysis),a quantitative method(topic modelling),and a sentimental *** study also looked at students’emotional states during and after the COVID-19 *** terms of determining trends in students’input,the results showed that quantitative and qualitative methods produced similar *** had unfavourable sentiments about studying during COVID-19 and positive sentiments about the face-to-face ***,topic modelling has revealed that the majority of difficulties are more related to the environment(home)and social *** were less accepting of online *** a result,it is possible to conclude that face-to-face study still attracts students and provides benefits that online study cannot,such as social interaction and effective eye-to-eye communication.
In recent years, privacy concerns have led to an increasing demand for secure data clustering algorithms that can protect sensitive data while maintaining the accuracy of the clustering results. By using homomorphic e...
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Building a hierarchical conceptual structure for smart health care, identifying the effects of distributed ledger technology on clever medical treatment, and then developing a system of applications for smart health c...
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Breast cancer diagnosis through mammography is a pivotal application within medical image-based diagnostics,integral for early detection and effective *** deep learning has significantly advanced the analysis of mammo...
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Breast cancer diagnosis through mammography is a pivotal application within medical image-based diagnostics,integral for early detection and effective *** deep learning has significantly advanced the analysis of mammographic images,challenges such as low contrast,image noise,and the high dimensionality of features often degrade model *** these challenges,our study introduces a novel method integrating Genetic Algorithms(GA)with pre-trained Convolutional Neural Network(CNN)models to enhance feature selection and classification *** approach involves a systematic process:first,we employ widely-used CNN architectures(VGG16,VGG19,MobileNet,and DenseNet)to extract a broad range of features from the Medical Image Analysis Society(MIAS)mammography ***,a GA optimizes these features by selecting the most relevant and least redundant,aiming to overcome the typical pitfalls of high *** selected features are then utilized to train several classifiers,including Linear and Polynomial Support Vector Machines(SVMs),K-Nearest Neighbors,Decision Trees,and Random Forests,enabling a robust evaluation of the method’s effectiveness across varied learning *** extensive experimental evaluation demonstrates that the integration of MobileNet and GA significantly improves classification accuracy,from 83.33%to 89.58%,underscoring the method’s *** detailing these steps,we highlight the innovation of our approach which not only addresses key issues in breast cancer imaging analysis but also offers a scalable solution potentially applicable to other domains within medical imaging.
Achieving high accuracy in time series forecasting (TSF) is challenging;particularly for series with inadequate training data or insignificant correlation among data. Modelling such time series with ANN based systems ...
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Scheduling tasks in overloaded real-time systems is a challenging problem that has received a significant amount of attention in recent years. The processor is overloaded with more tasks than its capacity, resulting i...
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One of the most significant and difficult tasks in the modern world is rainfall forecast. Rainfall is a complicated and nonlinear phenomenon that requires sophisticated computer modeling and simulation to anticipate w...
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The strategic behavior of users is significantly influenced by their hidden information such as private valuations, risk preferences, and price sensitivities. Contextual behavioral model learning refers to learning th...
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