This research work proposes an efficient framework to improve multispectral image classification through convolutional neural networks (CNNs) with optimized hyperspectral band selection. Hyperspectral images contain e...
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Autonomous driving has been one of the most promising research lines in the last decade. Although still far off the sought-after level 5, the research community shows great advancements in one of the most challenging ...
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ISBN:
(纸本)9789897586521
Autonomous driving has been one of the most promising research lines in the last decade. Although still far off the sought-after level 5, the research community shows great advancements in one of the most challenging tasks: the 3d perception. The rapid progress of related fields like Deep Learning is one the reasons behind this success. This enables and improves the processingalgorithms for the input data provided by LiDAR, cameras, radars and such other devices used for environment perception. With such growing knowledge, reviewing and structuring the state-of-the-art solutions becomes a necessity in order to correctly address future research directions. This paper provides a comprehensive survey of the progress of 3D object detection in terms of sensor data, available datasets, top-performing architectures and most notable frameworks that serve as a baseline for current and upcoming works.
The proceedings contain 87 papers. The topics discussed include: Auto-FP: an experimental study of automated feature preprocessing for tabular data;Data-CASE: grounding data regulations for compliant data processing s...
ISBN:
(纸本)9783893180950
The proceedings contain 87 papers. The topics discussed include: Auto-FP: an experimental study of automated feature preprocessing for tabular data;Data-CASE: grounding data regulations for compliant data processingsystems;data coverage for detecting representation bias in image datasets: a crowdsourcing approach;balancing utility and fairness in submodular maximization;stateful entities: object-oriented cloud applications as distributed dataflows;learning over sets for databases;a new PET for data collection via forms with data minimization, full accuracy and informed consent;adaptive compression for databases;analysis of open government datasets from a data design and integration perspective;fine-grained geo-obfuscation to protect workers’ location privacy in time-sensitive spatial crowdsourcing;and a framework to evaluate early time-series classification algorithms.
Objective image quality assessment measures were extensively used to evaluate the performance of different imageprocessing and analysis algorithms. However, they are application-driven. In contrast, subjective assess...
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The proceedings contain 180 papers. The topics discussed include: analysis of medical data and machine-learning algorithms from the perspective of public-goods models of data-provision decision making;price competitio...
The proceedings contain 180 papers. The topics discussed include: analysis of medical data and machine-learning algorithms from the perspective of public-goods models of data-provision decision making;price competition for service provision with different bargaining abilities;survey on stakeholder cooperative behavior for designing voluntary medical data provision motivation mechanisms;analysis of excellent service systems from co-creation and emergent synthesis perspective;meta-heuristic scheduling auction applying distributed genetic algorithm;the impact of characteristic function of Shapley value mechanism in distributed machine learning environment for equipment diagnosis;automatic measurement of timber diameter using imageprocessing;intelligent scheduling based on discrete-time simulation using machine learning;and a fuzzy synthesis approach for hierarchical decision analysis to select optimum repair technique.
Visual pollution is a significant obstacle in the modern era, where the world is advancing towards increasingly diverse inventions. These inventions require a suitable environment to achieve accurate outcomes. Artific...
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ISBN:
(纸本)9783031664304;9783031664311
Visual pollution is a significant obstacle in the modern era, where the world is advancing towards increasingly diverse inventions. These inventions require a suitable environment to achieve accurate outcomes. Artificial intelligence has already permeated all fields and interests of life;similarly, visual pollution also needs to be addressed properly. Visual pollution often creates obstacles in performing various tasks. To mitigate these issues, an artificial intelligence-based model will play a vital role. This work deals with detecting visual pollution using an artificial intelligence-based algorithm to apply practical solutions that enhance urban public scenery. In the first step, a dataset is chosen from an authorized organization;specifically, the data is sourced from Mendeley, named the Saudi Arabia Public Roads Visual Pollution Dataset 2023. The second step involves data scaling and background removal from training images to facilitate learning in AI models. In the third step, the dataset is processed using Random Forest and support vector machine algorithms to visualize the model's accuracy results. The support vector machine demonstrates better performance compared to the Random Forest.
This research focuses on the application of artificial intelligence in the modern design field and proposes a solution to build an information visualisation design platform based on natural language processing technol...
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Inspection of aircraft skin is required as per the Corrosion Prevention and Control Program (CPCP) to ensure aircraft structural integrity. Human visual inspection is the most widely used technique in aircraft surface...
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The yield estimation task altogether relies upon the way toward identifying and checking the quantity of fruits on trees. In production of fruit, basic yield the board choices are guided by bloom intensity, i.e., the ...
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The proceedings contain 16 papers. The topics discussed include: artificial intelligence for the future of construction;cobots and industrial robots;predictive maintenance for wind turbine bearings: an MLOps approach ...
The proceedings contain 16 papers. The topics discussed include: artificial intelligence for the future of construction;cobots and industrial robots;predictive maintenance for wind turbine bearings: an MLOps approach with the DIAFS machine learning model;development of an artificial intelligence tool and sensing in informatization systems of mobile robots;PCA-NuSVR framework for predicting local and global indicators of tunneling-induced building damage;design and deployment of data development toolkit in cloud manufacturing environments;research and development of imageprocessingalgorithms for effective recognition of various gestures in real time;machine learning models for the recognition of commands in smart home technologies;responsive dehydration: sensor-driven optimisation of production cycles in a solar dehydrator;and formation of the method of description and control of the relative position of the links of the upper limbs of the grip of an anthropomorphic robot.
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