The spotlight on large population-based studies is growing within the research community. Epidemiological studies, amassing extensive data through questionnaires and check-ups, often include imaging data like magnetic...
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Cat skin illnesses have traditionally been diagnosed manually, which can be laborious and arbitrary. Researchers offer a novel solution to this problem that utilizes Max Pooling layers and neural networks based on con...
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The long history of facial expression analysis has influenced current research and public interest. The scientific study and comprehension of emotion are credited to Charles Darwin's 19th-century publication The R...
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The proceedings contain 245 papers. The topics discussed include: a comprehensive analysis on deep learning based image retrieval;research on the influences of network characteristics of digital economy industry based...
ISBN:
(纸本)9798350323795
The proceedings contain 245 papers. The topics discussed include: a comprehensive analysis on deep learning based image retrieval;research on the influences of network characteristics of digital economy industry based on big data intelligent analysis algorithm;plant leaf disease classification using modified SVM with postprocessing techniques;a study of logistics teaching based on multimodal information input;feature extraction strategy of translated text based on neural network;localization recommendation algorithm of online translation course based on deep neural network;performance analysis of load balancing mechanism in cloud computing;pending interest table control management with optimal forwarder selection in named data network;big data analytics in small and medium enterprises;investigation and analyses of data processing through sports using scripting language: a novel paradigm;application of artificial neural network technology in electricity marketing;an accurate detection of drowsiness using a graph-based neural network;investigation on multi-objective optimization system of wastewater treatment process based on artificial intelligence;and ensemble machinelearning techniques for pancreatic cancer detection.
Early detection identified by dermoscopy images significantly decreases the mortality rate from skin cancer. However, the accuracy of the system diagnosis is impacted by multiple factors. A significant issue in this p...
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Aims: In the modern era, substance abuse is a global problem. CDC’s (Centre for Disease Control) National Center for Health statistics reported in July 2021 that, more than 93000 drug overdose deaths occurred alone i...
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The proceedings contain 16 papers. The special focus in this conference is on Complex Computational Ecosystems. The topics include: Modeling Ecosystem Management Based on the Integration of image Analysis and Human Su...
ISBN:
(纸本)9783031443541
The proceedings contain 16 papers. The special focus in this conference is on Complex Computational Ecosystems. The topics include: Modeling Ecosystem Management Based on the Integration of image Analysis and Human Subjective Evaluation - Case studies with Synecological Farming;on the Provision of Network-Wide Cyber Situational Awareness via Graph-Based Analytics;metrics for Evaluating Interface Explainability Models for Cyberattack Detection in IoT Data;machinelearning Model Applied to Higher Education;modeling El Niño and La Niña Events Using Evolutionary Algorithms;estimation of Seismic Phase Delays Using Evolutionary Algorithms;new Siamese Neural Networks for Text Classification and Ontologies Alignment;theorizing, Modeling and Visualizing Business Ecosystems. What Should Be Done?;A Comparative study of YOLO V4 and V5 Architectures on Pavement Cracks Using Region-Based Detection;evolutionary Reduction of the Laser Noise Impact on Quantum Gates;short Time Series Forecasting Method Based on Genetic Programming and Kalman Filter;performance Upgrade of Sequence Detector Evolution Using Grammatical Evolution and Lexicase Parent Selection Method;fuzzy pattern Trees with Pre-classification;models for the Computational Design of Microfarms.
Biometrics are being extensively used in person authentication;while spoofing is used by the imposters to crack into the biometric systems. The paper deals with the fingerprint image classification into two classes vi...
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The recent exponential surge in the number of vehicles on our roadways has made congestion and violations important problems. By automating traffic management using an ALPR system, we can improve access control system...
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ISBN:
(数字)9798350361780
ISBN:
(纸本)9798350361797
The recent exponential surge in the number of vehicles on our roadways has made congestion and violations important problems. By automating traffic management using an ALPR system, we can improve access control systems, streamline traffic flow, and save time. Here, we look at how well algorithms for edge processing and morphological processing perform. The parameters of the neural network, including the regularisation parameter, the count of hidden layer units, and the count of iterations, are optimised with great care. With a focus on real-time implementation and control via a graphical user interface, this case presents a parking security system suitable for usage in office buildings, institutions, malls, etc. Operating on Raspberry Pi 2B and Matlab, the system accomplishes a 97% efficiency rate through the use of imageprocessing techniques and machinelearning algorithms.
The observation of the advancing and retreating pattern of polar sea ice cover stands as a vital indicator of global warming. This research aims to develop a robust, effective, and scalable system for classifying pola...
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ISBN:
(纸本)9798350364613;9798350364606
The observation of the advancing and retreating pattern of polar sea ice cover stands as a vital indicator of global warming. This research aims to develop a robust, effective, and scalable system for classifying polar sea ice as thick/snow-covered, young/thin, or open water using Sentinel-2 (S2) images. Since the 52 satellite is actively capturing high-resolution imagery over the earth's surface, there are lots of images that need to be classified. One major obstacle is the absence of labeled 52 training data (images) to act as the ground truth. We demonstrate a scalable and accurate method for segmenting and automatically labeling S2 images using carefully determined color thresholds. We employ a parallel workflow using PySpark to scale and achieve 9-fold data loading and 16-fold map-reduce speedup on auto-labeling S2 images based on thin cloud and shadow filtered color-based segmentation to generate label data. The auto-labeled data generated from this process are then employed to train a U-Net machinelearning model, resulting in good classification accuracy. As training the U-Net classification model is computationally heavy and time-consuming, we distribute the U-Net model training to scale it over 8 GPLJs using the Horovod framework over a DGX cluster with a 7.2 lx speedup without affecting the accuracy of the model. Using the Antarctic's Ross Sea region as an example, the U-Net model trained on autolabeled data achieves a classification accuracy of 98.97% for auto-labeled training datasets when the thin clouds and shadows from the S2 images are filtered out.
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