Artificial Intelligence Tools and Applications in Embedded and Mobile Systems, Gebunden
Artificial Intelligence Tools and Applications in Embedded and Mobile Systems
- Selected Papers from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), 24-25 November 2022, Arusha, Tanzania
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Jorge Marx Gómez, Anael Elikana Sam, Devotha Godfrey Nyambo
- Verlag:
- Springer, 06/2024
- Einband:
- Gebunden, HC runder Rücken kaschiert
- Sprache:
- Englisch
- ISBN-13:
- 9783031565755
- Artikelnummer:
- 11907547
- Umfang:
- 288 Seiten
- Gewicht:
- 600 g
- Maße:
- 241 x 160 mm
- Stärke:
- 22 mm
- Erscheinungstermin:
- 30.6.2024
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
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Klappentext
Improving Robustness of Optimized Parameters Gradient Tree Boosting for Crime Forecast Model.- Evidence Based Practices On Co-Operative Societies Information Record Management.- Influence of Microservice Design Patterns for Data Science Workflows.- A systematic literature review toward standardization of business rules discovery in the context of Process Mining.- Contextual Multi-view Graph Community Detection using Graph Neural Networks.- Feature Selection Approach To Improve Malaria Diagnosis Model's Performance For High And Low Endemic Areas Of Tanzania.- 2-Stage Hybrid Ensemble Based Heterogeneous Committee Machine for Improving Soil Fertility Status Prediction Performance.- Convolutional Neural Network deep learning model for early detection of streak virus and lethal necrosis in maize: A case of Northern-highlands, Tanzania.- Object Detection Model for Poultry Diseases Diagnostics.- Machine Learning Model for Predicting Construction Project Success in Tanzania.- Improved MedicalImaging Transfer learning through the conflation of domain features.- Determining Emotion Intensities From Audio Data Using A Convolutional Neural Network.- Machine Learning Based Forward Collision Avoidance System: A Case study for the Kayoola EVS.- Visualizing Outlier Explanations for Mixed-type Data.- A Dolutegravir-Associated Hyperglycemia Computational Prediction Tool for People Living with HIV in Uganda.- Extraction of Numerical Facts from German Texts to enrich Internal Audit Data.- From Process Mining to Enterprise Mining.- CNN With Attention Guided Concatenation For Improved Image Restoration.- A Contribution to the Development of Sustainable Target Value Streams with Machine Learning Considering Material Flow Cost.- Mask R-CNN model for banana diseases segmentation.- The artificial neural network-based smart number plate for vehicles with real-time traffic signs recognition and notification.- Intermodal matching algorithm including public transportation and ride-hailing.- A Machine Learning-Based IoT Environmental Monitoring Platform for Data Centres
Biografie (Jorge Marx Gómez)
Prof. Dr. Jorge Marx Gomez ist Professor für Wirtschaftsinformatik an der Carl von Ossietzky Universität Oldenburg.