The proceedings contain 28 papers. The topics discussed include: machinelearning algorithms: a conceptual review;rural buildings and their technical concerns – a case study;concrete block with earth filled plastic w...
ISBN:
(纸本)9798350336771
The proceedings contain 28 papers. The topics discussed include: machinelearning algorithms: a conceptual review;rural buildings and their technical concerns – a case study;concrete block with earth filled plastic water bottle;a conceptual introduction of machinelearning algorithms;a study on MANET: along with recent trends, applications, types, protocols, goals, challenges;localized indoor / outdoor lora network a review;cancer detection: a review using fuzzy based learning system;human activity recognition using deep learning: past, present and future;impact of digital transformation in sourcing & tender management processes on employee job satisfaction - a study on Malaysian multinational electricity company;description of image using deep learning;digital competencies in blockchain technology;and real-time surveillance system for women’s safety and crime detection in public area.
This research presents a novel method that combines machinelearning and computer vision for simultaneous vehicle speed estimation, color detection, and mood estimation. Our system aims to improve road safety and opti...
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Cloud computing (CC) is a massive breakthrough in Information Technology (IT) that provides end users to access flexible andvirtualizedsources at affordable infrastructure cost and management. One of the most signific...
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Given increased complex data with high dimensions, feature selection aims to select a subset of features to increase the efficiency of machinelearning. This paper proposes a new feature selection method based on memb...
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ISBN:
(纸本)9783031779404;9783031779411
Given increased complex data with high dimensions, feature selection aims to select a subset of features to increase the efficiency of machinelearning. This paper proposes a new feature selection method based on membrane computing. The proposed method has two main advantages. First, it provides a new solution to search for feature combinations while requiring no model construction (which is time-consuming) to evaluate a feature subset. Second, feature selection is embedded in a membrane clustering algorithm, which is designed to enable searching for the best feature subset and finding active cluster centres at the same time. The designed clustering algorithm mimics the behavior of multiple cells and it has stronger global search ability than existing evolutionary algorithms. The efficacy of the proposed method has been shown by the evaluation of a set of benchmark data sets.
The number of multimedia services in modern fixed and mobile networks is growing day by day. Quality of service assessment is an important indicator for both the service provider and the end user. The article describe...
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This literature review explores the various research on the diagnosis of Lewy body dementia (LBD) and its difficulties, along with the challenges involved in training deep learning models-our research review process w...
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The proceedings contain 118 papers. The topics discussed include: hate speech detection using transformers;tweet analysis: what changed over time?;analysis of transfers learning techniques for early detection and grad...
ISBN:
(纸本)9798350348347
The proceedings contain 118 papers. The topics discussed include: hate speech detection using transformers;tweet analysis: what changed over time?;analysis of transfers learning techniques for early detection and grading of diabetic retinopathy on retinal images;FarmWise: crop cultivation analysis using image recognition and ArcGIS mapping;systematic literature review of rainforest surveillance;flood location, management and solution(FLMS): a flood prediction and management system for Kurla;machinelearning technique for crop selection and prediction of crop cultivation;vision based floating garbage classification using SIFT;is LinkedIn going to become the next Facebook?;MSMEs readiness for adopting artificial intelligence and machinelearning;and multimodal emotion recognition in video, audio, and text using deep and transfer learning.
Deep learning methodologies can be used for computer vision application. Early detection of disease in crops is critical for producing profitable crop yield. To detect diseases in tomato and potato plant leaves, a con...
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This study explores unsupervised learning methods for consumer segmentation - mean shift, hierarchical, and k-means clustering - in the context of vital business-customer interactions. Focused on addressing the escala...
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Image classification is a computer vision task that helps to classify the images based on various techniques with respect to feature extraction process. This research work is put together into two tasks. First, it aim...
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