There are several current systems developed to identify common skin lesions such as eczema that utilize image processing and most of these apply feature extraction techniques and machinelearning algorithms. These sys...
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ISBN:
(纸本)9781467386753
There are several current systems developed to identify common skin lesions such as eczema that utilize image processing and most of these apply feature extraction techniques and machinelearning algorithms. These systems extract the features from pre-processed images and use them for identifying the skin lesions through machinelearning as the core. This paper presents the design and evaluation of a system that implements a multi-model, multi-level system using the Artificial Neural Network (ANN) architecture for eczema detection. In this work, multi-model system is defined as architecture with different models depending on the input characteristic. The outputs of these models are integrated by a decision layer, thus multi-level, which computes the probability of an eczema case. The resulting system has 68.37% average confidence level as opposed to the 63.01% of the single level, i.e. single model, system in the actual testing of eczema versus non-eczema cases. Furthermore, the multi-model, multi-level design produces more stable models in the training phase wherein overfitting was reduced.
The Inter-Class Word Similarities in combination with Intra-Class Variations make it a difficult task for an OCR or any other machinelearning system to recognize the handwritten characters and words with high accurac...
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The proceedings contain 26 papers. The special focus in this conference is on Soft Computing in Data Science. The topics include: Time series machinelearning: Implementing ARIMA and hybrid ARIMA-ANN for electricity f...
ISBN:
(纸本)9789811072413
The proceedings contain 26 papers. The special focus in this conference is on Soft Computing in Data Science. The topics include: Time series machinelearning: Implementing ARIMA and hybrid ARIMA-ANN for electricity forecasting modeling;a design of a reminiscence system for tacit knowledge recall and transfer;pattern search based on particle swarm optimization technique for block matching motion estimation algorithm;enhancing parallel self-organizing map on heterogeneous system architecture;geovisualization using hexagonal tessellation for spatiotemporal earthquake data analysis in Indonesia;Incremental filtering visualization of jobstreet Malaysia ICT jobs;software application for analyzing photovoltaic module panel temperature in relation to climate factors;budget visual: Malaysia budget visualization;fuzzy arithmetical modeling of pressurizer in a nuclear power plant;road lane segmentation using deconvolutional neural network;nitrogen fertilizer recommender for paddy fields;Ranking performance of modified fuzzy TOPSIS variants based on different similarity measures;prediction of new bioactive molecules of chemical compound using boosting ensemble methods;Pragmatic miner to risk analysis for intrusion detection (PMRA-ID);intelligent system E-learning modeling according to learning styles and level of ability of students;mining textual terms for stock market prediction analysis using financial news;content quality of latent dirichlet allocation summaries constituted using unique significant words;rare event prediction using similarity majority under-sampling technique;patternrecognition of balinese carving motif using learning vector quantization (LVQ);Feature extraction for image content retrieval in thai traditional painting with SIFT algorithms;modeling of the gaussian-based component analysis on the kernel space to extract face image.
The proceedings contain 95 papers. The special focus in this conference is on Data Warehousing and Mining, machinelearning, Mobile and Ubiquitous Computing, AI, E-commerce and Distributed Computing and Soft Computing...
ISBN:
(纸本)9783319119328
The proceedings contain 95 papers. The special focus in this conference is on Data Warehousing and Mining, machinelearning, Mobile and Ubiquitous Computing, AI, E-commerce and Distributed Computing and Soft Computing, Evolutionary Computing, Bio-inspired Computing and *** topics include: Approximation neural network for phoneme synthesis;pattern-matching for speaker verification;online clustering algorithm for restructuring user web search results;optimal computer based analysis for detecting malarial parasites;a survey of dynamic program analysis techniques and tools;extended self organizing map with probabilistic neural network for pattern classification problems;fuzzy rule-based adaptive proportional derivative controller;sentence completion using text prediction systems;architectural recommendations in building a network based secure, scalable and interoperable internet of things middleware;mean interleaved round robin algorithm;cryptanalysis of image encryption based on permutation-substitution using chaotic map and Latin square image cipher;windowed Huffman coding with limited distinct symbols by least recently used symbol removable;theme interception sequence learning;energy efficient distributed topology control technique with edge pruning;dynamic cache resizing in flashcache;heuristic for context detection in time varying domains;construction of automated concept map of learning using hashing technique;analysis of estimation techniques for feature based navigation of unmanned air vehicles;curved videotext detection and extraction;an approach to utilize FMEA for autonomous vehicles to forecast decision outcome;diffusion and encryption of digital image using genetic algorithm;character recognition using teaching learning based optimization;the fuzzy robust graph coloring problem;detection of moving object and image steganography using integer wavelet transform based on color space approach.
The proceedings contain 55 papers. The special focus in this conference is on Information and Communication Technology and Applications. The topics include: Application of Supervised machinelearning Based on Gaussian...
ISBN:
(纸本)9783030691424
The proceedings contain 55 papers. The special focus in this conference is on Information and Communication Technology and Applications. The topics include: Application of Supervised machinelearning Based on Gaussian Process Regression for Extrapolative Cell Availability Evaluation in Cellular Communication Systems;anomaly Android Malware Detection: A Comparative Analysis of Six Classifiers;Credit Risk Prediction in Commercial Bank Using Chi-Square with SVM-RBF;A Conceptual Hybrid Model of Deep Convolutional Neural Network (DCNN) and Long Short-Term Memory (LSTM) for Masquerade Attack Detection;An Automated Framework for Swift Lecture Evaluation Using Speech recognition and NLP;DeepFacematch: A Convolutional Neural Network Model for Contactless Attendance on e-SIWES Portal;hausa Intelligence Chatbot System;an Empirical Study to Investigate Data Sampling Techniques for Improving Code-Smell Prediction Using Imbalanced Data;a Statistical Linguistic Terms Interrelationship Approach to Query Expansion Based on Terms Selection Value;application of Big Data Analytics for Improving learning Process in Technical Vocational Education and Training;validation of Student Psychological Player Types for Game-Based learning in University Math Lectures;outlier Detection in Multivariate Time Series Data Using a Fusion of K-Medoid, Standardized Euclidean Distance and Z-Score;an Improved Hybridization in the Diagnosis of Diabetes Mellitus Using Selected Computational Intelligence;optimizing the Classification of Network Intrusion Detection Using Ensembles of Decision Trees Algorithm;identification of Bacterial Leaf Blight and Powdery Mildew Diseases Based on a Combination of Histogram of Oriented Gradient and Local Binary pattern Features;feature Weighting and Classification Modeling for Network Intrusion Detection Using machinelearning Algorithms;comparative Performance Analysis of Anti-virus Software.
We explore the use of Wav2Vec 2.0, NeMo, and ESPNet models trained on a dataset in Macedonian language for the development of Automatic Speech recognition (ASR) models for low-resource languages. The study aims to eva...
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ISBN:
(数字)9783031390593
ISBN:
(纸本)9783031390586;9783031390593
We explore the use of Wav2Vec 2.0, NeMo, and ESPNet models trained on a dataset in Macedonian language for the development of Automatic Speech recognition (ASR) models for low-resource languages. The study aims to evaluate the performance of recent state-of-the-art models for speech recognition in low-resource languages, such as Macedonian, where there are limited resources available for training or fine-tuning. The paper presents a methodology used for data collection and preprocessing, as well as the details of the three architectures used in the study. The study evaluates the performance of each model using WER and CER metrics and provides a comparative analysis of the results. The findings of the research showed that Wav2Vec 2.0 outperformed the other models for the Macedonian language with a WER of 0.21, and CER of 0.09, however, NeMo and ESPNet models are still good candidates for creating ASR tools for low-resource languages such as Macedonian. The research presented provides insights into the effectiveness of different models for ASR in low-resource languages and highlights the potentials for using these models to develop ASR tools for other languages in the future. These findings have significant implications for the development of ASR tools for other low-resource languages in the future, and can potentially improve accessibility to speech recognition technology for individuals and communities who speak these languages.
The proceedings contain 67 papers. The special focus in this conference is on Innovations in Computing Research. The topics include: Exploratory Analysis of Gamblers’ Financial Transactions to Mine Behavior...
ISBN:
(纸本)9783031655210
The proceedings contain 67 papers. The special focus in this conference is on Innovations in Computing Research. The topics include: Exploratory Analysis of Gamblers’ Financial Transactions to Mine Behavioral pattern Data;The Detection of Misstated Financial Reports Using XBRL Mining and Intelligible MLP;university Student Enrollment Prediction: A machinelearning Framework;early Prediction of Sepsis Utilizing Multi-branches Multi-tasks Hybrid Deep learning Model;comprehensive Analysis of Iris Dataset Using K-Mean and Fuzzy K-Mean Clustering Algorithm;An Efficient and Reliable scRNA-seq Data Imputation Method Using Variational Autoencoders;Prediction of Automotive Vehicles Engine Health Using MLP and LR;medical Image Character recognition Using Attention-Based Siamese Networks for Visually Similar Characters with Low Resolution;toward Smart Bicycle Safety: Leveraging machinelearning Models and Optimal Lighting Solutions;vThrot: Fine-Grained, Virtual I/O Resource Redistribution Scheme;Bayesian Optimization-Based CNN Model for Blood Glucose Estimation Using Photoplethysmography Signals;comparing Convolutional Neural Networks and Transformers in a Points-of-Interest Experiment;Gender and Age Extraction from Audio Signal Using Convolutional Neural Network, MFCC and Spectrogram;The Hybrid Model Combination of Deep learning Techniques, CNN-LSTM, BERT, Feature Selection, and Stop Words to Prevent Fake News;comparative Analysis of Decision Tree Algorithms Using Gini and Entropy Criteria on the Forest Covertypes Dataset;A Comparative Analysis of Random Forest and Support Vector machine Techniques on the UNSW-NB15 Dataset;a Comparative Study of Speed Measurement Using Radar Guns and Pneumatic Counter;Comparative Analysis of Preprocessing Techniques for KNN Classification on the Diabetes Dataset;code Smells for Assessing and Improving Students’ Coding Skills and Practices;Analysis of eSIM/iSIM for Critical Communications.
The proceedings contain 54 papers. The special focus in this conference is on Advanced Computing and Intelligent Engineering. The topics include: Wavelet Transform Domain Methods for Resolution Enhancement of Satellit...
ISBN:
(纸本)9789811510809
The proceedings contain 54 papers. The special focus in this conference is on Advanced Computing and Intelligent Engineering. The topics include: Wavelet Transform Domain Methods for Resolution Enhancement of Satellite Images;improving Query Results in Ontology-Based Case-Based Reasoning by Dynamic Assignment of Feature Weights;a Survey on Representation for Itemsets in Association Rule Mining;efficient Clustering Using Nonnegative Matrix Factorization for Gene Expression Dataset;design of Random Forest Algorithm Based Model for Tachycardia Detection;detection of Spam in YouTube Comments Using Different Classifiers;deep learning Architectures for Named Entity recognition: A Survey;effect of Familiarity on recognition of Pleasant and Unpleasant Emotional States Induced by Hindi Music Videos;early Detection of Breast Cancer Using Support Vector machine With Sequential Minimal Optimization;the Case Study of Brain Tumor Data Analysis Using Stata and R;predictive Data Analytics for Breast Cancer Prognosis;a Semantic Approach of Building Dynamic Learner Profile Model Using WordNet;prioritizing Public Grievance Redressal Using Text Mining and Sentimental Analysis;an Automatic Summarizer for a Low-Resourced Language;printed Odia Symbols for Character recognition: A Database Study;importance of Data Standardization Methods on Stock Indices Prediction Accuracy;Feature Relevance Analysis and Feature Reduction of UNSW NB-15 Using Neural Networks on MAMLS;video Summarization Based on Optical Flow;Decision Support System for Black Classification of Dental Images Using GIST Descriptors;clustering Performance Analysis;pattern Analysis of Brain Functional Connectivity Parameters After Removal of Artifactual Motifs from EEG During Meditation;Hyper-heuristic Image Enhancement (HHIE): A Reinforcement learning Method for Image Contrast Enhancement.
Excessive alcohol consumption leads to inebriation. Driving under the influence of alcohol is a criminal offence in many countries involving operating a motor vehicle while inebriated to a level that renders safely op...
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ISBN:
(纸本)9783031064272;9783031064265
Excessive alcohol consumption leads to inebriation. Driving under the influence of alcohol is a criminal offence in many countries involving operating a motor vehicle while inebriated to a level that renders safely operating a motor vehicle extremely difficult. Studies show that traffic accidents will become the fifth most significant cause of death if inebriated driving is not mitigated. Inversely, 70% of the world population can be protected by mitigating inebriated driving. Short term effects of inebriation include lack of balance, inhibition and fine motor coordination, dilated pupils and slow heart rate. An ideal inebriation recognition method that operates in real-time is less intrusive, more convenient, and efficient. Deep learning has been used to solve object detection, object recognition, object tracking and image segmentation problems. In this paper, we compare deep learning inebriation recognition methods. We implemented Faster R-CNN and YOLO methods for our experiment. We created our dataset of sober and inebriated individuals made available to the public. Six thousand four hundred forty-three (6443) face images were used, and our best performing pipeline was YOLO with a 99.6% accuracy rate.
This paper presents a digital watermarking technology for guaranteeing the database integrity. The proposed scheme based on the fragile watermarking technique, exploits trained support vector regression (SVR) predicti...
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ISBN:
(纸本)9780769529943
This paper presents a digital watermarking technology for guaranteeing the database integrity. The proposed scheme based on the fragile watermarking technique, exploits trained support vector regression (SVR) predicting function to distribute the digital watermark over the particular numeric attributes to achieve embedding and detecting watermark by the same SVR predicting function. If the absolute value of the difference between predicted value and attribute value is more than the designed fixed value, like one, then the database content will be tampered with.
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