the proceedings contain 76 papers. the topics discussed include: a method for Chinese sarcasm detection based on enhanced cross-entropy and regularization;CNN-BiGRU-attention: a time series-based traffic flow predicti...
ISBN:
(纸本)9798350355925
the proceedings contain 76 papers. the topics discussed include: a method for Chinese sarcasm detection based on enhanced cross-entropy and regularization;CNN-BiGRU-attention: a time series-based traffic flow prediction model;inevitable exposure: analyzing the privacy paradox in the age of digital connectivity with machine learning paradigms;research on data fusion algorithms for non-stop overload detection on highways;deep learning based automatic detection algorithm of atrial fibrillation implemented on FPGA;the effect of data transformation techniques on machine learning performance: a case study on student dropout prediction;a novel semi-supervised learning method using causal margin adaptation for imbalanced classification;and revolutionizing requirements elicitation: deep learning-based classification of functional and non-functional requirements.
the proceedings contain 85 papers. the topics discussed include: on the computation of the number of bubbles and tunnels of a 3-D binary object;interval coded scoring index with interaction effects - a sensitivity stu...
ISBN:
(纸本)9789897581731
the proceedings contain 85 papers. the topics discussed include: on the computation of the number of bubbles and tunnels of a 3-D binary object;interval coded scoring index with interaction effects - a sensitivity study;an experimental evaluation of the adaptive sampling method for time series classification and clustering;foreground segmentation for moving cameras under low illumination conditions;a new family of bounded divergence measures and application to signal detection;classifier ensembles with trajectory under-sampling for face re-identification;nonparametric Bayesian line detection - towards proper priors for robotic computer vision;similarity function learning with data uncertainty;similarity assessment as a dual process model of counting and measuring;hidden Markov random fields and direct search methods for medical image segmentation;adding model constraints to CNN for top view hand pose recognition in range images;and a mobile indoor positioning system founded on convolutional extraction of learned WLAN fingerprints.
Protein-Protein Interaction (PPI) provides important insights into the metabolic mechanisms of different biological processes. Although PPIs in some organisms have been investigated systematically, PPIs in the ocean a...
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ISBN:
(纸本)9798400712203
Protein-Protein Interaction (PPI) provides important insights into the metabolic mechanisms of different biological processes. Although PPIs in some organisms have been investigated systematically, PPIs in the ocean archaea remain largely unexplored. But such species have special investigation value since their adaptation to extreme living conditions may generate unique PPIs. In this paper, we aim to characterize and predict PPIs in ocean archaea to advance understanding of their metabolic networks. First, we collect all ocean archaea PPIs with high confidence from STRING database and analyze the PPI network features, including centrality and enrichment analysis. the functional enrichment results of the largest connecting subgraph in the PPI network show most PPIs in our constructed dataset is related to the translation and transcription processes. then, we generate an equal number of negative PPI pairs, whose members have either different subcellular locations or GO terms. We also use the generated dataset to test the performance of three pretraining methods and their ensemble methods in the binary PPI prediction task. Our results suggest the ensemble methods could be applied to further improve models’ performance. Fine-tuned models trained on the ocean archaea dataset are expected to predict the other ocean archaea PPIs that are not included in the STRING database and get more understanding about the ocean archaea PPI universe.
the proceedings contain 214 papers. the topics discussed include: application of massive parallel computation based q-learning in system control;dynamic policy programming with descending regularization for efficient ...
ISBN:
(纸本)9781665499163
the proceedings contain 214 papers. the topics discussed include: application of massive parallel computation based q-learning in system control;dynamic policy programming with descending regularization for efficient reinforcement learning control;multi-attribute context-aware item recommendation method based on deep learning;carbon trading based on quadratic modal decomposition and recurrent neural network price prediction model;vision transformer is required for hyperspectral semantic segmentation;adaptive gated spatial-temporal network for traffic prediction;remaining useful life prediction method based on the improved holt double exponential model;pedestrian re-identification after enhancing textural features based on parallel residual network;dynamic gesture recognition method based on millimeter-wave radar;training agent to play Pac-Man under authentic environment based on image recognition;a multi-factor prediction model for carbon productivity based on stacking integration method;one-step multi-view clustering based on low-rank tensor proximity learning;CAGSF: optimization algorithm for network representation learning based on the community structure;and the positive effect of attention module in few-shot learning for plant disease recognition.
the proceedings contain 19 papers. the topics discussed include: building segmentation from remote sensing image via dwt attention networks;reconstructing 3D shapes as an union of boxes from multi-view images;three-di...
ISBN:
(纸本)9781450399968
the proceedings contain 19 papers. the topics discussed include: building segmentation from remote sensing image via dwt attention networks;reconstructing 3D shapes as an union of boxes from multi-view images;three-dimensional sphere recognition and tracking based on YOLO;LLFormer: an efficient and real-time LiDAR lane detection method based on transformer;frequency-split inception transformer for image super-resolution;MSYOLOF: multi-input-single-output encoder network with tripartite feature enhancement for object detection;exploration of transfer learning capability of multilingual models for text classification;policy updating methods of Q learning for two player bargaining game;multi-population Runge Kutta optimizer based on Gaussian disturbance;survey of the formal verification of operating systems in power monitoring system;and a study on the line loss index of a substation area based on cooperative games with multiple influencing factors.
the advent of 6G wireless technology heralds a new era of network optimization driven by AI/ML algorithms across its entirety. As outlined in 3GPP TS 28.104 (Release 19), Management Data Analytics (MDA) presents diver...
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ISBN:
(数字)9798331532970
ISBN:
(纸本)9798331532987
the advent of 6G wireless technology heralds a new era of network optimization driven by AI/ML algorithms across its entirety. As outlined in 3GPP TS 28.104 (Release 19), Management Data Analytics (MDA) presents diverse use cases and requirements. However, the variety of data formats and AI/ML application methods introduces complexity and limits generic implementation. Compounded by the exponential deployment of cells and a range of new devices like XR devices, UAVs, etcs., the resulting data deluge poses a formidable big-data challenge for 5G advanced, 6G, and beyond. Anticipating the unique demands of 6G, characterized by metaverse-enabled networking and AR/VR applications, there arises a need for AI/ML-driven visual data processing services. this paper presents a novel approach: representing wireless network data in the form of images and videos. Such a representation not only optimizes storage and processing requirements but also facilitates the reuse of AI/ML models across various use cases and data formats. Experimental validation is provided through two key avenues: Firstly, text-based logs are transformed into images, enabling the identification of recurrent issues through visual patternrecognition. Secondly, Comma Seperated Variables (CSV) data is converted into a series of images, effectively simulating video frames, thus extending the realm of video analytics to encompass all data types pertinent to self-optimizing networks in 6G RAN. the advantages of this image and video-based data representation paradigm are meticulously elucidated, offering a compelling proposition for the future landscape of wireless network optimization in 6G and beyond.
the proceedings contain 178 papers. the topics discussed include: automatic optimization of variational quantum algorithm-based classifiers;transfer learning for ensembles: reducing computation time and keeping the di...
ISBN:
(纸本)9781450396899
the proceedings contain 178 papers. the topics discussed include: automatic optimization of variational quantum algorithm-based classifiers;transfer learning for ensembles: reducing computation time and keeping the diversity;a simple semi-supervised joint learning framework for few-shot text classification;deep learning-based sentiment analysis for social media;a prediction model of diabetes based on ensemble learning;can mental illness lead to dismissal? from a causal machine learning perspective;express-related counterfeit cigarette crime prediction with imbalanced data-based machine learning techniques;event extraction in vertical domain based on similar semantics and dependency syntax;effective training-time stacking for ensembling of deep neural networks;research on radar corrosion prediction model based on bp neural network optimized by genetic algorithm;a differential privacy K-means algorithm for improving privacy budget allocation;and support-based neural network ensemble method for predicting the SoH of lithium-ion battery.
Cricket, one of the world’s most popular sports, has developed considerably during the past few decades. the competition and complexity of this sport increased largely during the past few years, which brought the att...
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ISBN:
(数字)9798331530983
ISBN:
(纸本)9798331530990
Cricket, one of the world’s most popular sports, has developed considerably during the past few decades. the competition and complexity of this sport increased largely during the past few years, which brought the attention of the researchers to develop technical solutions to improve the quality of the sport by improving boththe on-field decision-making and practicing methods. there are several kinds of high-end equipment available in the market that can be used to improve these skills. Even though such equipment can be used at the national level, it is very difficult to use them at school and club levels due to their higher cost. this research focused on enhancing the batting skills of cricket batsmen using a low-cost setup that uses webcams to capture the footage and the MediaPipe library, which was developed by Google to analyze motion data. this research analyzed two cricket shots, the front foot defence, and the pull shot, using four web cameras. the received footage was analyzed using MediaPipe to identify the variations in the angles of the player’s left elbow and left shoulder while playing the shot. these pattern identifications can help successfully understand the angle variation of the forward foot defence and the pull shots by generating an average angle value graph using four web cameras. these graphs show the special patterns for each batting shot. this methodology and the results are valuable for developing a successful player analyzing system by considering the other important cricket shots at a very low cost with affordable 2D web cameras.
the proceedings contain 31 papers. the special focus in this conference is on Recent Trends in Image Processing and patternrecognition. the topics include: Image Processing and patternrecognition of Micropores of Po...
ISBN:
(纸本)9783031235986
the proceedings contain 31 papers. the special focus in this conference is on Recent Trends in Image Processing and patternrecognition. the topics include: Image Processing and patternrecognition of Micropores of Polysulfone Membrane for the Bio-separation of Viruses from Whole Blood;An Extreme Learning Machine-Based AutoEncoder (ELM-AE) for Denoising Knee X-ray Images and Grading Knee Osteoarthritis Severity;motor Imagery Classification Combining Riemannian Geometry and Artificial Neural Networks;Autism Spectrum Disorder Detection Using Transfer Learning with VGG 19, Inception V3 and DenseNet 201;shrimp Shape Analysis by a Chord Length Function Based Methodology;supervised Neural Networks for Fruit Identification;targeted Clean-Label Poisoning Attacks on Federated Learning;building Marathi SentiWordNet;A Computational Study on Calibrated VGG19 for Multimodal Learning and Representation in Surveillance;alzheimer’s Disease Detection Using Ensemble Learning and Artificial Neural Networks;automated Deep Learning Based Approach for Albinism Detection;a Deep Learning-Based Regression Scheme for Angle Estimation in Image Dataset;the Classification of Native and Invasive Species in North America: A Transfer Learning and Random Forest Pipeline;Towards a Digital Twin Integrated DLT and IoT-Based Automated Healthcare Ecosystem;enabling Edge Devices Using Federated Learning and Big Data for Proactive Decisions;ioT and Blockchain Oriented Gender Determination of Bangladeshi Populations;Federated Learning Based Secured Computational Offloading in Cyber-Physical IoST Systems;a Hybrid Campus Security System Combined of Face, Number-Plate, and Voice recognition;single-Trial Detection of Event-Related Potentials with Artificial Examples Based on Coloring Transformation;identifying the Relationship Between Hypothesis and Premise;semi-supervised Multi-domain Learning for Medical Image Classification;data Poisoning Attack by Label Flipping on SplitFed Learning;a Deep Learning-Powered
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