
Intelligent Systems and Pattern Recognition
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
This Three-volume set CCIS 2303-2305 constitutes the proceedings of the 4th International Conference on Intelligent Systems and Pattern Recognition, ISPR 2024, held in Istanbul, Turkey, in June 26-28, 2024.
The 77 full papers presented were thoroughly reviewed and selected from the 210 submissions. The conference provided an interdisciplinary forum for the exchange of innovative advancements in the fields of artificial intelligence and pattern recognition.
More details
Other editions
Additional editions

Content
.- Deep Learning Approach for Tunisian Postal Address Segmentation.
.- Leveraging DQN-Based Recommender Systems for E-Commerce in Smart Cities.
.- Empowering Healthcare with Deep Learning: An Application for Early Detection of Skin Cancer.
.- GAN-Enhanced Deep Learning Approach for Forecasting the Potentially Toxic Cyanobacteria in Dams.
.- Adaboost optimized by sinh cosh algorithm for prediction of software defects.
.- Prediction of Chronic Diseases using Parallel 1D-CNN Feature Extraction and SVM Classification based on SMOTE.
.- Interpretable Ensemble Learning Model For Enabling An IDS To Detect DNS Attacks.
.- An Improved Static Analysis Approach for Malware Detection by Optimizing Feature Extraction Combining Different ML Algorithms.
.- Deep learning algorithms for colon cancer detection: A comparative study with traditional machine learning methods.
.- Diabetic Retinopathy Grade Assessment using ResNetRS.
.- Novel hybrid feature selection method and globalization technique for text classification.
.- Applying Machine Learning Approaches with Integrated Internet of Things for Water Management System.
.- Implementation of a comparative study of convolutional neural network architectures for image blind noise elimination.
.- Structuring and Text Summarization of Indian Legal Documents.
.- Photovoltaic Cell Defect Classification Using Attention U-Net Image Segmentation.
.- Ulcerative Colitis Image Classification using Federated Deep Learning.
.- Accelerating Traditional Object Detection Methods on Sophisticated Embedded Systems.
.- Detecting Raspberry Ripeness Across Different Growth Stages Using YOLOv8.
.- Air Quality Forecasting in Presence Missing Data.
.- Image Encryption in Frequency Domain using Hybrid Chaotic Maps, Hashing, and Lifting Wavelet Transform.
.- Detection and parameter estimation of an inflatable boat.
.- Self-Attention Siamese Network for Unsupervised Few-Shot Learning Tasks.
.- Comparative study using ensemble methods and sampling techniques for imbalanced diabetes data.
.- Advanced Deep Learning Techniques for Accurate Detection of Wheat Leaf Diseases.
.- Enhancing Tomato Crop Health: Leveraging Modified InceptionResNetV2 for Disease Detection.
.- BA-GAN: A Boundary-Aware Generative Adversarial Network for Document Restoration.
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.