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| Autore: |
Mercier-Laurent Eunika
|
| Titolo: |
Computational Intelligence in Data Science : 8th IFIP TC 12 International Conference, ICCIDS 2025, Chennai, India, February 12–14, 2025, Revised Selected Papers, Part I / / edited by Eunika Mercier-Laurent, Bhuvana Jayaraman, Priyadharsini Ravisankar, Angel Deborah S., Anusha Jayasimhan
|
| Pubblicazione: | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 |
| Edizione: | 1st ed. 2026. |
| Descrizione fisica: | 1 online resource (518 pages) |
| Disciplina: | 006.312 |
| Soggetto topico: | Data mining |
| Application software | |
| Artificial intelligence | |
| Image processing - Digital techniques | |
| Computer vision | |
| Computers | |
| Data Mining and Knowledge Discovery | |
| Computer and Information Systems Applications | |
| Artificial Intelligence | |
| Computer Imaging, Vision, Pattern Recognition and Graphics | |
| Computing Milieux | |
| Altri autori: |
JayaramanBhuvana
RavisankarPriyadharsini
SAngel Deborah
JayasimhanAnusha
|
| Nota di contenuto: | -- Computer Vision for Real World Applications. -- AI-Enhanced breast cancer diagnosis (BCD) using machine learning models with GA-SA Hybrid. -- Efficient Medicinal Plant Leaf Classification Using MobileNet Architecture: A Deep Learning Approach. -- SAVER: A Cost-Effective Drone-Based Object Detection and Thermal Mapping System for Enhanced Emergency Response. -- Anchors as Building Blocks: A Detailed survey of Scene Graph Decomposition and Captioning. -- Signxv8 For Realtime Sign Language Translation. -- Advanced Multi-Class Brain Tumor Segmentation Using Deep Learning Architectures. -- EduVid: Transforming Educational Text into Engaging Videos. -- Optimizing the Hyperparameters for Classification of Lung Diseases from Chest X-ray Images. -- ResUNet-AttnASPP – A novel ResUNet architecture with Atrous Spatial Pyramid Pooling (ASPP) and attention gates for efficient brain tumor segmentation. -- Leveraging Convolutional Neural Networks for Gait Recognition and Individual Identification for improved neurological care. -- Deep Learning for Enhanced Delineation and Classification in Brain MRI Images. -- EfficientNetB1-Based Model for Brain Tumor Classification in MRI. -- FoodWise: Diabetes-Friendly Nutrition Guide for Traditional Indian Dishes. -- The Amphibian and Reptiles Classification from Camera Trap Images Using Deep Learning. -- Deciphering the Intricacies of Pancreatic Malignancy Through Advanced Deep Learning Methodologies. -- Beam Light Detection and Intensity Analysis using Computer Vision. -- Deep CNN Based Image Classifier for Home CCTV Monitoring System to Detect Intruders. -- Optimizing Terrain Classification with Multi-Spectral Imaging Using Machine Learning Models. -- Empirical Analysis of Deep Learning Models for Multinational Currency Detection. -- Real-Time Sign Language Recognition and Multilingual Translation Using Ensemble Deep Neural Networks and TensorFlow’s MoveNe. -- Automated Melanoma Detection using integrated Neural network architectures. -- A Hybrid Deep Learning Framework for Image Deblurring and Colorization using CNNs and GANs. -- PawsitivelyYours: A Comprehensive Approach to Detect Canine Atopic Dermatitis. -- Attention Integrated DenseNet121 based U-Net Model for Efficient Segmentation using LGG Tumor data. -- Deep Convolutional Neural Network Model For Predicting Alzheimer’s Disease. -- Automatic Comic Converter From Videos. -- Efficient Channel Attention Based CNN For Skin Disease Classification. -- Satellite Image Analysis Using Convolution Neural Networks For Environmental Monitoring. -- Backend Optimization and Face Recognition in Real-Time Surveillance using DeepFace. |
| Sommario/riassunto: | The three-volume set IFIP ICCIDS 748, 749 and 750 constitutes the refereed post-conference proceedings of the 8th IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2025, held in Chennai, India, during February 12–14, 2025. The 91 papers including 70 regular papers and 21 short papers included in these proceedings were carefully reviewed and selected from 317 submissions. The papers are organized in the following topical sections: Part I: Computer Vision for Real World Applications. Part II: Computer Vision for Real World Applications; Emerging Trends in AI for Speech and Text. Part III: Emerging Trends in AI for Speech and Text; Computational Intelligence for Secure, Smart and Sustainable Applications. |
| Titolo autorizzato: | Computational Intelligence in Data Science ![]() |
| ISBN: | 3-031-98356-4 |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9911047654503321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |