Sensors Data Processing Using Machine Learning
Materialtyp:
ArtikelUtgivningsinformation: MDPI - Multidisciplinary Digital Publishing Institute 2024Beskrivning: 1 electronic resource (248 p.)Innehållstyp: - text
- computer
- online resource
- 9783725811717
- 9783725811724
- Computing and Information Technology
- Computer science
- 3DCNN
- AVC
- Apple M1
- Apple M2
- Arduino-based module
- BERT
- BERTimbau
- COVID-19
- ConvLSTM
- CoreML
- CutPaste-Mix
- DistilBERT
- DistilBERTimbau
- H.264
- H.265
- HEVC
- IoT
- IoT nodes
- IoT-based system
- NPU benchmark
- QoE
- QoS
- Raspberry Pi
- big data
- classification model
- connected and automated mobility
- connectivity data
- convolutional neural network
- cooperative
- data augmentation
- deep learning
- defect classification
- detection of degrees of toxicity
- discrete state transition algorithm
- ductile cast iron pipe
- feature fusion
- grey correlation analysis
- human activity recognition
- indoor navigation
- infrastructure readiness assessment
- lexicon approach
- machine learning
- mobile application
- neural engine
- neural processing cores
- neural processing unit
- packet loss rate
- positioning data
- pre-trained model
- processor architectures
- rare earth extraction
- remote sensing classification
- sample selection method
- sample size
- sarcasm detection
- self-supervised
- sentiment classification
- smart classrooms
- smart systems
- student learning behavior
- teaching evaluation system
- t
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The main aim of this reprint was to collect research focusing on data processing using machine learning and deep learning. We invited investigators to contribute both original and review articles, covering the research and development in the areas of data processing using machine learning (ML) and deep learning (DL). These areas include solutions that are designed for smart devices. In this reprint, leading experts in the field share their insights, research findings, and visions for the future. Together, we embark on a journey to unlock the potential of effective data processing that involves transforming data from a given format into a more usable and desirable form, rendering them more meaningful and informative. Machine learning (ML), deep learning (DL), and artificial intelligence (AI) have proven to be effective methods for this purpose. Through the utilization of machine learning algorithms, mathematical modeling, or various statistical techniques, the entire process can be automated.
Creative Commons Licence cc by-nc-nd cc https://creativecommons.org/licenses/by-nc-nd/4.0/
eng
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