The aim of this work was to develop an AI-controlled fitness trainer to tend to each user’s needs. It includes an AI-based voice assistant that acts as a virtual fitness trainer to guide the user in performing a cert...
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A crime is an act that merits public condemnation and penalties, which is usually in the form of a fine or jail. It is a widespread social issue that affects a country's life style, economic progress, and credibil...
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Face recognition system has become an integral part of the security mechanisms used in the IoT applications. Smart cities and industries started deploying face recognition applications for security purposes through su...
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With the development of science and technology worldwide, computer technology has gradually been widely used in various fields like the military and biomedical domains. In this situation, people's requirements for...
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ISBN:
(数字)9789811924484
ISBN:
(纸本)9789811924484;9789811924477
With the development of science and technology worldwide, computer technology has gradually been widely used in various fields like the military and biomedical domains. In this situation, people's requirements for image recognition are increasing. However, the efficiency of manual image recognition is very low, and image recognition has always been a weak field in computer technology. This paper will introduce various deep learning models such as feedforward neural networks, convolutional neural networks, and recurrent neural networks. We will talk about how these models work and then compare and analyze these different networks. In this paper, we will try to train a convolutional neural network from a data set. The "dogs-vs-cats" data set from Kaggle will be used. In the "dogs-vs-cats" experiment part, some basic tasks in image processing will be discussed, such as feature extraction method, which is one of the most important steps in each link of image processing. Finally, the machine should be able to distinguish between pictures of dogs and cats. Moreover, we will also discuss some preliminary applications of deep learning in image recognition.
The proceedings contain 73 papers. The topics discussed include: road traffic status discrimination method based on data fusion of multiple floating vehicles;traffic sign reflectivity detection method based on driver&...
ISBN:
(纸本)9781510666559
The proceedings contain 73 papers. The topics discussed include: road traffic status discrimination method based on data fusion of multiple floating vehicles;traffic sign reflectivity detection method based on driver's visual recognition;a belief propagation cooperative localization algorithm in GNSS-loss environments;an integrated algorithm of transparency retrieval;research on 5G differential protection data compression transmission technology;optimization of radiation shielding scheme for Jupiter spacecraft based on genetic algorithm;bidirectional consistency of multi-agent based on data-driven;research on mung bean variety identification algorithm based on machinelearning and hyperspectral technology;research and analysis of blockchain system based on computer big data model;and deep clustering model for time-series data based on recurrence plot and variational auto-encoder.
The proceedings contain 18 papers. The special focus in this conference is on Information Technologies and Intelligent Decision Making Systems. The topics include: Comparative Analysis of Traditional machinelearning ...
ISBN:
(纸本)9783031603174
The proceedings contain 18 papers. The special focus in this conference is on Information Technologies and Intelligent Decision Making Systems. The topics include: Comparative Analysis of Traditional machinelearning Approaches for Time Series Clustering Under Colored Noise;on the Open Transport data Analysis Platform;investigation of the Characteristics of a Frequency Diversity Array Antenna;comparative Analysis of Fuzzy Controllers in a Truck Cruise Control System;implementation of a Blockchain-Based Software Tool to Verify the Authenticity of Paper Documents;development of Methods and Algorithms for Dimension Reduction of Space Description for patternrecognition Problem;service for Checking Students’ Written Work Using a Neural Network;implementing a Jenkins Plugin to Visualize Continuous Integration Pipelines;elimination of Optical Distortions Arising from In Vivo Investigation of the Mouse Brain;quantum Fourier Transform in Image Processing;choosing an Information Protection Mechanism Based on the Discrete Programming Method;application of machinelearning Methods for Annotating Boundaries of Meshes of Perineuronal Nets;diagnostics of Animals Diseases Based on the Principles of Neutrosophic Sets and Sugeno Fuzzy Inference;the Technique of Processing Non-Gaussian data Based on Artificial Intelligence;development of Automation and Control System of Waste Gas Production Process Based on Information Technology;machinelearning and datamining.
Recent advances in neural networks have enabled them to become powerful tools in data processing for tasks such as patternrecognition and classification. This has enabled neural networks to be applied to large-scale ...
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With the rapid development of machinelearning methods, deep learning models based on big data and computer arithmetic are widely used in various scenarios, including target detection and image recognition. In order t...
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This paper presents a comprehensive approach to predicting student engagement and learning behavior by analyzing eye-tracking data combined with behavioral analysis using camera-based recognition algorithms. The propo...
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ISBN:
(数字)9798331525439
ISBN:
(纸本)9798331525446
This paper presents a comprehensive approach to predicting student engagement and learning behavior by analyzing eye-tracking data combined with behavioral analysis using camera-based recognition algorithms. The proposed system leverages WebGazer for eye-tracking to monitor gaze patterns and uses computer vision algorithms to recognize behaviors and emotional states. Feelings like engagement, frustration, or perplexity are identified using facial expression analysis. The system aims to provide real-time, actionable insights to students and educators by relating to emotional and concentration states by combining different modalities, thereby improving personalized learning strategies and educational outcomes.
This paper studies the reliable navigation problem in stochastic transportation networks with uncertain topology. The objective is to find a dynamic routing policy, which navigates the ego vehicle to the destination w...
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