Motion segmentation plays an important role in many applications including autonomous driving, computer vision and robotics. Previous works mainly focus on segmenting objects from seen videos. In this paper, we presen...
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The proceedings contain 26 papers. The special focus in this conference is on Optimization, Learning Algorithms and Applications. The topics include: Pest Detection in Olive Groves Using YOLOv7 and YOLOv8 Mo...
ISBN:
(纸本)9783031530357
The proceedings contain 26 papers. The special focus in this conference is on Optimization, Learning Algorithms and Applications. The topics include: Pest Detection in Olive Groves Using YOLOv7 and YOLOv8 Models;Using LiDAR Data as Image for AI to Recognize Objects in the Mobile Robot Operational Environment;an Evaluation of Image Preprocessing in Skin Lesions Detection;an Artificial Intelligence-Based Method to Identify the Stage of Maturation in Olive Oil Mills;vehicle Industry Big Data Analysis Using Clustering Approaches;enhancing Forest Fire Detection and Monitoring Through Satellite Image recognition: A Comparative Analysis of Classification Algorithms Using Sentinel-2 Data;An Efficient GPU Parallelization of the Jaya Optimization Algorithm and Its Application for Solving Large Systems of Nonlinear Equations;Multi-objective Optimal Sizing of an AC/DC Grid Connected Microgrid System;sub-system Integration and Health Dashboard for Autonomous Mobile Robots;movement patternrecognition in Boxing Using Raw Inertial Measurements;optimization Models for Hydrokinetic Energy Generated Downstream of Hydropower Plants;deep Conditional Measure Quantization;fault Classification of Wind Turbine: A Comparison of Hyperparameter Optimization Methods;Assessing the Reliability of AI-Based Angle Detection for Shoulder and Elbow Rehabilitation;deep Learning and Machine Learning Techniques Applied to Speaker Identification on Small Datasets;performance of Heuristics for Classifying Leftovers from Cutting Stock Problem;Deep Learning-Based Classification and Quantification of Emulsion Droplets: A YOLOv7 Approach;identification of Late Blight in Potato Leaves Using Image Processing and Machine Learning;adaptive Convolutional Neural Network for Predicting Steering Angle and Acceleration on Autonomous Driving Scenario;Impact of EMG Signal Filters on Machine Learning Model Training: A Comparison with Clustering on Raw Signal;assessing the 3D Position of a Car with a Single 2D Camera Usin
Engineering education accreditation emphasizes the cultivation of students' ability to solve complex engineering problems, including the cultivation of students' ability to analyze, design and develop solution...
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The proceedings contain 26 papers. The special focus in this conference is on Optimization, Learning Algorithms and Applications. The topics include: Pest Detection in Olive Groves Using YOLOv7 and YOLOv8 Mo...
ISBN:
(纸本)9783031530241
The proceedings contain 26 papers. The special focus in this conference is on Optimization, Learning Algorithms and Applications. The topics include: Pest Detection in Olive Groves Using YOLOv7 and YOLOv8 Models;Using LiDAR Data as Image for AI to Recognize Objects in the Mobile Robot Operational Environment;an Evaluation of Image Preprocessing in Skin Lesions Detection;an Artificial Intelligence-Based Method to Identify the Stage of Maturation in Olive Oil Mills;vehicle Industry Big Data Analysis Using Clustering Approaches;enhancing Forest Fire Detection and Monitoring Through Satellite Image recognition: A Comparative Analysis of Classification Algorithms Using Sentinel-2 Data;An Efficient GPU Parallelization of the Jaya Optimization Algorithm and Its Application for Solving Large Systems of Nonlinear Equations;Multi-objective Optimal Sizing of an AC/DC Grid Connected Microgrid System;sub-system Integration and Health Dashboard for Autonomous Mobile Robots;movement patternrecognition in Boxing Using Raw Inertial Measurements;optimization Models for Hydrokinetic Energy Generated Downstream of Hydropower Plants;deep Conditional Measure Quantization;fault Classification of Wind Turbine: A Comparison of Hyperparameter Optimization Methods;Assessing the Reliability of AI-Based Angle Detection for Shoulder and Elbow Rehabilitation;deep Learning and Machine Learning Techniques Applied to Speaker Identification on Small Datasets;performance of Heuristics for Classifying Leftovers from Cutting Stock Problem;Deep Learning-Based Classification and Quantification of Emulsion Droplets: A YOLOv7 Approach;identification of Late Blight in Potato Leaves Using Image Processing and Machine Learning;adaptive Convolutional Neural Network for Predicting Steering Angle and Acceleration on Autonomous Driving Scenario;Impact of EMG Signal Filters on Machine Learning Model Training: A Comparison with Clustering on Raw Signal;assessing the 3D Position of a Car with a Single 2D Camera Usin
Current violence detection systems often face challenges such as high computational costs, real-time processing difficulties, and limited precision in detecting violent activities in dynamic environments. This researc...
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ISBN:
(数字)9798331527549
ISBN:
(纸本)9798331527556
Current violence detection systems often face challenges such as high computational costs, real-time processing difficulties, and limited precision in detecting violent activities in dynamic environments. This research addresses these issues by proposing a hybrid deep learning model that integrates MobileNetV2 for efficient spatial feature extraction and ConvLSTM (Convolutional Long Short-Term Memory) for capturing temporal patterns. The model effectively discriminates between aggressive and non-aggressive behaviours in real-time video streams. Using the Kaggle Violence Dataset, which comprises 1,000 video clips of violent and non-violent activities, the system achieved an accuracy of 96%, showcasing its high performance. Additionally, an integrated alert system enhances practical application by sending real-time notifications via a Telegram bot, including details such as location, timestamp, and camera ID. This solution ensures timely responses to violent incidents, addressing the core issues of computational efficiency and real-time precision, while offering scalability and applicability in diverse scenarios.
Clustering intra-urban areas with the same pollution characteristics can help to accurately manage intra-urban air pollution. In this study, a new classification model for PM 2.5 -O 3 composite pollution features is ...
Clustering intra-urban areas with the same pollution characteristics can help to accurately manage intra-urban air pollution. In this study, a new classification model for PM 2.5 -O 3 composite pollution features is established based on tensor decomposition and spectral clustering methods. The tensor decomposition was utilized to extract pollution features from massive air pollutant concentration data, and the pollution concentration data were decomposed into day-by-day, intra-day, and spatial modes, which provided a low-dimensional space for the subsequent spectral clustering and fine clustering classification process of the urban spatial-scale PM 2.5 -O 3 composite pollution conditions. The model is explored by taking the annual PM 2.5 and O 3 pollution conditions in Beijing in 2017 and 2020 as an example, discussing the differences in geographic locations and pollution characteristics between the different models, and explaining the changes in the city’s pollution characteristics from 2017 to 2020. Through this new hybrid method, scientific support can be provided for urban refinement and precise management.
Document images are now widely captured by handheld devices such as mobile phones. The OCR performance on these images are largely affected due to geometric distortion of the document paper, diverse camera positions a...
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ISBN:
(纸本)9783030865498
Document images are now widely captured by handheld devices such as mobile phones. The OCR performance on these images are largely affected due to geometric distortion of the document paper, diverse camera positions and complex backgrounds. In this paper, we propose a simple yet effective approach to rectify distorted document image by estimating control points and reference points. After that, we use interpolation method between control points and reference points to convert sparse mappings to backward mapping, and remap the original distorted document image to the rectified image. Furthermore, control points are controllable to facilitate interaction or subsequent adjustment. We can flexibly select post-processing methods and the number of vertices according to different application scenarios. Experiments show that our approach can rectify document images with various distortion types, and yield state-of-the-art performance on real-world dataset. This paper also provides a training dataset based on control points for document dewarping. Both the code and the dataset are released at https://***/gwxie/Document-Dewarping-with-Control-Points.
The proceedings contain 78 papers. The special focus in this conference is on Recent Trends in Image Processing and patternrecognition. The topics include: Ensemble of Nested Dichotomies for Author Identification Sys...
ISBN:
(纸本)9789811604928
The proceedings contain 78 papers. The special focus in this conference is on Recent Trends in Image Processing and patternrecognition. The topics include: Ensemble of Nested Dichotomies for Author Identification System Using Similarity-Based Textual Features;Feature Combination of Pauli and H/A/Alpha Decomposition for Improved Oil Spill Detection Using SAR;a Fast and Efficient Convolutional Neural Network for Fruit recognition and Classification;copy-Move Image Forgery Detection Using Discrete Wavelet Transform;a Comprehensive Survey of Different Phases for Involuntary System for Face Emotion recognition;classification of Vehicle Type on Indian Road Scene Based on Deep Learning;indian Road Lanes Detection Based on Regression and clustering using Video Processing Techniques;detection of Emotion Intensity Using Face recognition;double Authentication System Based on Face Identification and Lipreading;fuzzy Approach to Evaluate Performance of Teaching Staff in Technical Institutions;safety Gear Check at Industries and Laboratories Using Convolutional Neural Network Based on Deep Learning;analysis of Changing Trends in Textual Data Representation;detection of Falsary Happening on Social Media Using Image Processing: Feature Extraction and Matching;Development of Multi Faces recognition System Using HOG Features and Neural Network Classifier in Real Time Environment;extraction of Key Frame from Random Videos Based On Discrete Cosine Transformation;Prediction of SO2 Air Pollution Quality Parameter of Kolhapur City Using Time Series Analysis;A Big Data Prediction for Weather Forecast Using Hybrid ARIMA-ANN Time Series Model;automatic Detection of Riots Using Deep Learning;protecting Big Data Sets from Unauthorized Users on Cloud;text Categorization: A Lazy Learning-Based Approach.
The proceedings contain 78 papers. The special focus in this conference is on Recent Trends in Image Processing and patternrecognition. The topics include: Ensemble of Nested Dichotomies for Author Identification Sys...
ISBN:
(纸本)9789811605062
The proceedings contain 78 papers. The special focus in this conference is on Recent Trends in Image Processing and patternrecognition. The topics include: Ensemble of Nested Dichotomies for Author Identification System Using Similarity-Based Textual Features;Feature Combination of Pauli and H/A/Alpha Decomposition for Improved Oil Spill Detection Using SAR;a Fast and Efficient Convolutional Neural Network for Fruit recognition and Classification;copy-Move Image Forgery Detection Using Discrete Wavelet Transform;a Comprehensive Survey of Different Phases for Involuntary System for Face Emotion recognition;classification of Vehicle Type on Indian Road Scene Based on Deep Learning;indian Road Lanes Detection Based on Regression and clustering using Video Processing Techniques;detection of Emotion Intensity Using Face recognition;double Authentication System Based on Face Identification and Lipreading;fuzzy Approach to Evaluate Performance of Teaching Staff in Technical Institutions;safety Gear Check at Industries and Laboratories Using Convolutional Neural Network Based on Deep Learning;analysis of Changing Trends in Textual Data Representation;detection of Falsary Happening on Social Media Using Image Processing: Feature Extraction and Matching;Development of Multi Faces recognition System Using HOG Features and Neural Network Classifier in Real Time Environment;extraction of Key Frame from Random Videos Based On Discrete Cosine Transformation;Prediction of SO2 Air Pollution Quality Parameter of Kolhapur City Using Time Series Analysis;A Big Data Prediction for Weather Forecast Using Hybrid ARIMA-ANN Time Series Model;automatic Detection of Riots Using Deep Learning;protecting Big Data Sets from Unauthorized Users on Cloud;text Categorization: A Lazy Learning-Based Approach.
With the advancement of new engineering, matrix computation is an indispensable mathematical tool in big data processing, which is widely used in the fields of image processing, machine learning, patternrecognition a...
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ISBN:
(纸本)9781665416672
With the advancement of new engineering, matrix computation is an indispensable mathematical tool in big data processing, which is widely used in the fields of image processing, machine learning, patternrecognition and so on. This paper aims to by means of interaction platform, such as MOOC, QQ Group and Rain Classroom, design the teaching mode of the matrix computation course to help students to learn how to solve the engineering problems. An example is given to show the applications of singular value decomposition in imaging pressing. Through the teaching practice of 2019-2020 academic year, the course of matrix computation integrates the advantages of online and offline teaching, and promote students' research ability and innovative spirit in the experimental process.
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