Information retrieval systems for the patent domain have a long history. they can support patent experts in a variety of daily tasks: from analyzing the patent landscape to support experts in the patenting process and...
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ISBN:
(纸本)9781450394086
Information retrieval systems for the patent domain have a long history. they can support patent experts in a variety of daily tasks: from analyzing the patent landscape to support experts in the patenting process and large-scale information extraction. Advances in machinelearning and natural language processing allow to further automate tasks, such as paragraph retrieval or even patent text generation. Uncovering the potential of semantic technologies for the intellectual property (IP) industry is just getting started. Investigating the use of artificial intelligence methods for the patent domain is therefore not only of academic interest, but also highly relevant for practitioners. Compared to other domains, high quality, semi-structured, annotated data is available in large volumes (a requirement for supervised machinelearning models), making training large models easier. On the other hand, domain-specific challenges arise, such as very technical language or legal requirements for patent documents. the focus of the 4th edition of this workshop will be on two-way communication between industry and academia from all areas of information retrieval in particular withthe Asian community. We want to bring together novel research results and the latest systems and methods employed by practitioners in the field.
the proceedings contain 11 papers. the special focus in this conference is on . the topics include: Analysis and Forecast of Energy Demand in Senegal with a SARIMA Model and an LSTM ...
ISBN:
(纸本)9783031423161
the proceedings contain 11 papers. the special focus in this conference is on . the topics include: Analysis and Forecast of Energy Demand in Senegal with a SARIMA Model and an LSTM Neural Network;moving Towards Blockchain-Based Methods for Revitalizing Healthcare Domain;design of a Tokenized Blockchain Architecture for Tracking Trade in the Global Defense Market;requirements for Interoperable Blockchain Systems: A Systematic Literature Review;PENN: Phase Estimation Neural Network on Gene Expression data;MRIAD: A Pre-clinical Prevalence Study on Alzheimer’s Disease Prediction through machinelearning Classifiers;exploring the Link Between Brain Waves and Sleep patterns with Deep learning Manifold Alignment;YOLOv5 for Automatic License Plate recognition in Smart Cities;an Investigation into Predicting Flight Fares in India Using machinelearning Models.
Artificial Intelligence (AI)-based emotion recognition using various kinds of data has attracted vast attention in recent years. Impressive results have been achieved, but only recently the influence of the training d...
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ISBN:
(数字)9781665490627
ISBN:
(纸本)9781665490627
Artificial Intelligence (AI)-based emotion recognition using various kinds of data has attracted vast attention in recent years. Impressive results have been achieved, but only recently the influence of the training data with its potential biases and variations in annotation quality are discussed. Still, the majority of the research literature focuses on improving machinelearning techniques and model performance using single data sets. Literature on the impact of training data remains scarce. therefore, in this paper we investigate the influence of the training data on the accuracy of recognizing emotional states in facial expressions by a comparative evaluation, using multiple established facial image databases. Results reveal inconsistencies in the data annotations as well as ambiguities in the emotional states expressed. thus, they allow to critically discuss data quality of the training data, contributing to a more in-depth understanding of previous emotion recognition approaches, and improving the design of more transparent AI solutions.
this paper studied the methods for improving the accuracy and efficiency of the action of power employees by deeply studying the application of neural network algorithm in power safety supervision video. Firstly, this...
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Cardio Vascular Disease (CVD) causes dysfunction in our heart and blood arteries, which frequently results in death or paralysis. therefore, many lives can be prevented by the early and automatic recognition of CVD. A...
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Over 50% of India's population is employed in agriculture, which is vital to the country's economy but confronts enormous hurdles from environmental variability. this study reviews machinelearning approaches ...
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the proceedings contain 90 papers. the topics discussed include: severity stratification of brinjal leaf diseases: a federated learning CNNs approach;experimental analysis of malware detection and classification syste...
ISBN:
(纸本)9798350384628
the proceedings contain 90 papers. the topics discussed include: severity stratification of brinjal leaf diseases: a federated learning CNNs approach;experimental analysis of malware detection and classification system using intelligent deep learning methodology;exploring the thematic clusters of artificial intelligence applications in supply chains using topic modelling and text mining: a machinelearning insight;predicting quality of ground water using different deep learning models;BananaLeafNet: federated learning CNNs for multiclass disease identification in banana crops;the detection of adverse drug reactions in clinical text data using transformer models;energy consumption forecasting in buildings based on heating and cooling loads using regression models;towards sustainable ICT: a bibliometric review of green communications;leveraging machinelearning approach for large-scale unstructured satellite image analysis: a comprehensive review and future predictions;and the food preservation using a solar dryer monitoring system.
Facial expressions are conveyed by changes in multiple facial action units, and their recognition relies on both local information and the contextual understanding of the whole face. We propose a global and local cons...
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the proceedings contain 172 papers. the topics discussed include: reconstruction optimization of economic operation of distribution network based on datamining algorithm;ROI segmentation for breast cancer classificat...
ISBN:
(纸本)9798350333558
the proceedings contain 172 papers. the topics discussed include: reconstruction optimization of economic operation of distribution network based on datamining algorithm;ROI segmentation for breast cancer classification : deep learning perspective;evaluation of hotspot performance in IoT enabled wireless sensor network using special intermediate nodes in the network;a university innovation and entrepreneurship information sharing platform based on datamining and classification algorithms;data governance based on full-service data analysis domain of power grid;minimum utilization of energy resource via MAC routing protocol for mobile sensor network;sentimental analysis of movie review based on naive bayes and random forest technique;parallel algorithm of high precision surface modeling based on differential geometry;maximization of achievable sum rate and improvement in outage probability in intelligent reflecting surface (IRS) driven NOMA networks;automated 20-20-20 timers using facial detection and facial recognition;enhancement of routing flexibility by a novel distributed approach for WSN;and improvement of reliable data transmission signal by space diversity technique in wireless communication.
the technology of named entity recognition has been gradually refined. However, current research is primarily focused on non-nested named entity recognition, with less attention devoted to nested named entity recognit...
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