Cloud computing (CC) is the demonstration of the technology that makes use of the substructure for computing in a proficient fashion. This sort of computing offers great quantity of consequences in augmenting the prod...
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Web usage mining is a crucial research area that aims to uncover user behavior patterns from web log data because web usage mining can be used to analyze a website’s usage. This study examined web usage mining to dis...
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The data collected from all the states and Union Territories has been compiled in the Publication, according to the ministry of road transport and roads transport research wing. The total number of accident-related de...
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The data collected from all the states and Union Territories has been compiled in the Publication, according to the ministry of road transport and roads transport research wing. The total number of accident-related deaths in 2018 was 1,51,417, which is a 2.3 percent increase over 2017. Around 85% of accident-related deaths occur in the 18-60 age range, which is the most productive. Road traffic fatalities not only inflict the relatives of the victims considerable emotional suffering, but they also cost the nation a lot of money. In this data maximum hazard happens due to delayed response of family and friends as they are unknown of the situation of the sight of the accident. Also, several cases remain unreported. Our objective is to reduce this number to make our nation strong and prosper. In this current research we are committed to creating a social network where road accidents can be reported quickly to family and friends, so the delayed response can be reduced. The practice of associating a person with a picture has become increasingly common thanks to the media. However, it is less resistant to retinal and fingerprint scanning. The face detection and recognition module created for the current research is described in this paper. Face detection will be performed using Haar-Cascades, while face identification will be performed using Eigenfaces, Fisher faces, and local binary pattern histograms.
Biosensors are analytical devices used to detect the presence of a specific bio-chemical substance (called analyte), through the combination of a biorecognition element with a physico-chemical transducer. Biosensors u...
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ISBN:
(纸本)9781665405331
Biosensors are analytical devices used to detect the presence of a specific bio-chemical substance (called analyte), through the combination of a biorecognition element with a physico-chemical transducer. Biosensors using field-effect transistor (FET) transducing platforms (called Bio-FETs) exploit the variations of the current between a source and a drain terminal upon specific (physical or chemical) interactions in presence of the analyte of interest. While Bio-FETs have mainly been used in various fields of application such as medical diagnostics, biomolecule detection (like glucose) and food safety, environmental monitoring is still a quite unexplored area. In particular for agricultural applications, it is extremely important to develop real-time, portable, and low-cost monitoring devices for various types of pesticides, especially considering that nowadays many of these are considered environmental contaminants and are being banned. Only recently some studies have reported the development of Bio-FETs for the detection of a particular type of pesticides: herbicides. In this review, we revise the use of Bio-FETs for environmental monitoring applications. First we highlight the working principles of Bio-FETs, presenting the most commonly used material and the possible device configurations. Then we present the most relevant studies employing Bio-FETs for environmental monitoring. Finally, we show a quite new approach for Bio-FET, which is the coupling of biosensors with artificial intelligence and machinelearning algorithms, to analyse complex data.
The proceedings contain 30 papers. The special focus in this conference is on Applied Intelligence and Informatics. The topics include: Key Techniques and Challenges for Processing of Heart Sound Signals;enhanced...
ISBN:
(纸本)9783030822682
The proceedings contain 30 papers. The special focus in this conference is on Applied Intelligence and Informatics. The topics include: Key Techniques and Challenges for Processing of Heart Sound Signals;enhanced Signal Processing Using Modified Cyclic Shift Tree Denoising;a machinelearning Driven Android Based Mobile Application for Flower Identification;a Generative Text Summarization Model Based on Document structure Neural Network;human Gender Detection from Facial Images Using Convolution Neural Network;few-Shot learning for Tamil Handwritten Character recognition Using Deep Siamese Convolutional Neural Network;A CNN Based Model for Venomous and Non-venomous Snake Classification;recognition of Dysfluency in Speech: A Bidirectional Long-Short Term Memory Based Approach;distributed Denial of Service Attack Detection Using machinelearning and Class Oversampling;glaucoma Detection Using Inception Convolutional Neural Network V3;scientific Metrological Analysis of Government Services Based on Big data Analysis and Visualization Software Driven by Information Technology;violent Video Event Detection: A Local Optimal Oriented pattern Based Approach;human Age Estimation Using Deep learning from Gait data;an Error Resilient Video Transmission in Ad Hoc Network Using Error Diffusion Block Truncation Coding;ALO: AI for Least Observed People;COVID-Hero: machinelearning Based COVID-19 Awareness Enhancement Mobile Game for Children;Literature Classification Model of Deep learning Based on BERT-BiLstM——Taking COVID-19 as an Example;identifying Relevant stakeholders in Digital Healthcare;COVID-19 Detection Using Chest X-Ray Images with a RegNet structured Deep learning Model;mixed Bangla-English Spoken Digit Classification Using Convolutional Neural Network;iConDet: An Intelligent Portable Healthcare App for the Detection of Conjunctivitis.
The diagnosis of interactions between two drugs is an essential procedure in drug development. Many medical tool's offer inclusive records related to DDI. However, this tool's results are not very satisfactory...
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Video/Camera-based monitoring is a prominent and difficult research problem in the field of machinelearning and patternrecognition and posed much interest in our safety in the private and public sectors. Therefore, ...
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ISBN:
(纸本)9783030822699;9783030822682
Video/Camera-based monitoring is a prominent and difficult research problem in the field of machinelearning and patternrecognition and posed much interest in our safety in the private and public sectors. Therefore, surveillance cameras have been deploying to control suspicious activity. Consequently, many researchers have worked on developing an automatic surveillance system to detect violent events and assists security guards to take the right decision at the right time. still, violent event detection is difficult to detect because of illumination, complex background, scale variation, blurriness, occlusion, and low resolution in a surveillance camera. In this paper, the Local Optimal Oriented pattern (LOOP) texture-based feature descriptor is proposed. Eventually, eminent features are used with a support vector machine (SVM) classier for violent event detection. Experiments are conducted on the Hockey Fight dataset and Violent-Flows dataset. The five-Fold Cross-Validation approach is used to analyze the performance of the proposed method. The data and results are promising and encouraging.
machinelearning (ML) is a subset of artificial intelligence domain that incorporates a wide range of techniques including Genetic algorithms, Artificial Neural Networks, Bayesian learning, decision trees. Analytical ...
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ISBN:
(纸本)9781665476560
machinelearning (ML) is a subset of artificial intelligence domain that incorporates a wide range of techniques including Genetic algorithms, Artificial Neural Networks, Bayesian learning, decision trees. Analytical learning and other supervised or unsupervised learning models. These techniques exploit present and arriving data to recognize the patterns and foresee forthcoming clinical events. There are number of evolving applications of ML in other aspects of patient management that have not yet been analyzed. Generative Adversarial networks (GANs), a deep neural networks which are capable of generating or transforming images and can support in faster imaging by creatingrealistic images utilizing the current imaging protocols in a variety of contrast and modalities. This paper deals with the big picture analysis of GAN along with architecture, comparison with existing approaches, application areas and the challenges associated with it.
The rapid growth of Distributed Generation (DG) is driven by the persistent need for electricity. Over time, nearly all DG sources are sustainable. Islanding is a significant issue that arises when there is an excessi...
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The proceedings contain 23 papers. The special focus in this conference is on Artificial Intelligence: Theories and Applications. The topics include: Convolution Neural Network Based Approach for Glaucoma Disease Dete...
ISBN:
(纸本)9783031285394
The proceedings contain 23 papers. The special focus in this conference is on Artificial Intelligence: Theories and Applications. The topics include: Convolution Neural Network Based Approach for Glaucoma Disease Detection;Deep Multi-Scale Hashing for Image Retrieval (DMSH);genetic Programming for Screen Content Image Quality Assessment;A Progressive Deep Transfer learning for the Diagnosis of Alzheimer’s Disease on Brain MRI Images;An Optimized MSER Using Bat Algorithm for Skin Lesion Detection;accurate Detection of Brain Tumor Using Compound Filter and Deep Neural Network;Bi-ESRGAN: A New Approach of Document Image Super-Resolution Based on Dual Deep Transfer learning;preface;expanding Convolutional Neural Network Kernel for Facial Expression recognition;a Novel Classification Method for Group Decision-Making Dimensions;intelligent Cache Placement in Multi-cache and One-Tenant Networks;enhanced Grey Wolf Optimizer for data Clustering;artificial Orca Algorithm for Solving University Course Timetabling Issue;global Automatic Tuning of Fuzzy Sliding Mode Controller for an Inverted Pendulum: A Genetic Solution;Intelligent ITSC Fault Detection in PMSG Using the machinelearning Technique;Series Elastic Actuator Cascade PID Controller Design Using Genetic Algorithm Method;Quantum Natural Language Processing: A New and Promising Way to Solve NLP Problems;learning More with Less data: Reaching the Power-Law Limits in steganalysis Using Larger Batch Sizes;offline Text-Independent Writer Identification Using Local Black pattern Histograms;Robust Method for Breast Cancer Classification Based on Feature Selection Using RGWO Algorithm;digital Modulation Classification Based on Automatic K-Nearest Neighbors Classifier.
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