
Machine Learning and Intelligent Communications
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
The 28 revised full papers were carefully selected from 58 submissions. The papers are organized thematically in tracks as follows: internet of vehicle communication system; applications of neural network and deep learning; intelligent massive MIMO communications; intelligent positioning and navigation systems; intelligent space and terrestrial integrated networks; machine learning algorithms and intelligent networks; image information processing.
More details
Other editions
Additional editions

Content
Deep learning network for Frequency offset Cancellation in OFDM communication system.- Research on the Rising Phenomenons in the Bit Error Rate Performances of LT-Based UEP codes.- Ensemble Classification Technique for Cultural Heritage Image.- Power Allocation for Sum Rate Maximization of Uplink Massive MIMO System with Maximum Ratio Combining.- Research on Indoor Passive Location Based on LoRa Fingerprint.- Application of Dijkstra algorithm in optimal route selection under the background of TPACK education model.- The Wave Filter Design of UFMC Vehicle Communication System.- Research on Image Binary Classification Based on Fast Style Transfer Data Enhancement.- 3DCNN Backed Conv-LSTM Auto Encoder for Micro Facial Expression Video Recognition.- Research on charge and discharge control strategy of supercapacitor.- Intelligent wheelchair based on medical health examination.- Research on Forest Fire Image Recognition System in Northeast Forest Region Based on Machine Vision.- Researchon Face Image Restoration Method Based on Improved WGAN.- Research on text communication security based on deep learning model.- Elimination of Network Intrusion using Advance Data Mining Technology.- Automatic Detection and Classification of Anti-Islamic Web Text-Contents.- Deep Learning Technique for Dessert Plant Classification and Recognition.- Sparse Algorithm for OFDM Underwater Acoustic Channel Estimation.- Improvement of CLAlgorithm in MIMO-OFDM System.- SD-based low-complexity signal detection algorithm in massive MIMO.- Improved YOLOv4 infrared image pedestrian detection algorithm.- Research on ECG Classification Method Based on Convolutional Neural Network.- A Servey on Meta-learning Based Few-shotClassification.- Image Retrieval Algorithm Based on Fractal Coding.- Research on Fractal Image Coding Method Based on SNAM Segmentation Scheme.- Aircraft Detection In Aerial Remote Sensing Images Based On Contrast Self-supervised Learning.- Fast fractal image compression algorithmbased on compression perception.- Color Image Fast Encryption Algorithm Based on JPEG encoding.- Review of Research on Speech Emotion Recognition.- Concentration Prediction Based on mRMRXGBoost Model.- An improved crowd counting method based on YOLOv3.
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.