Vor Ort
Merkzettel Warenkorb
Produktbild: Advances in Brain Inspired Cognitive Systems
Band 15498 - 10%

Advances in Brain Inspired Cognitive Systems 14th International Conference, BICS 2024, Hefei, China, December 6–8, 2024, Proceedings, Part II

Aus der Reihe Lecture Notes in Artificial Intelligence
10% sparen

61,99 € UVP 69,54 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

11.03.2025

Herausgeber

Amir Hussain + weitere

Verlag

Springer Singapore

Seitenzahl

297

Maße (L/B/H)

23,5/15,5/1,8 cm

Gewicht

482 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9628-84-1

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

11.03.2025

Herausgeber

Verlag

Springer Singapore

Seitenzahl

297

Maße (L/B/H)

23,5/15,5/1,8 cm

Gewicht

482 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9628-84-1

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: GPSR Kontakt

Ein neues Kapitel für Ihre Bücher

Ein neues Kapitel für Ihre Bücher

Schenken Sie Ihren alten Schätzen ein zweites Leben und erhalten dafür eine Thalia Geschenkkarte.

Jetzt verkaufen
Jetzt verkaufen

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Advances in Brain Inspired Cognitive Systems

  • .- Multi-Modal Dynamic Information Selection Pyramid Network for Alzheimer’s Disease Classification.

    .- Text-Guided Vision Mamba for Alzheimer’s Disease Prediction using 18F-FDG PET.

    .- EEG-based Recognition of Knowledge Acquisition States in Second Language Learning.

    .- A study on the neural mechanism of the spatial position of speech in different masking types affecting auditory attention processing.

    .- DSCF-DE: A Query-based Object Detection Model via Dynamic Sampling and Cascade Fusion.

    .- MDFNet: Multi-Dimensional Fusion Attention for Enhanced Image Captioning.

    .- Dynamic Points Location of Professional Model Pose Based on Improved Network Stacking Model.

    .- A Redundancy Free Facial Acne Detection Framework Based on Multi-view Dermoscopy Images Stitching.

    .- A New Device Placement Approach with Dual Graph Mamba Networks and Proximal Policy Optimization.

    .- Cross-Generational Contrastive Continual Learning for 3D point cloud semantic segmentation.

    .- TGAM-SR: A Sequential Recommendation Model for Long And Short-Term Interests Based on TCN-GRU And Atten-tion Mechanism.

    .- Investigating ChatGPT’s Translation Hallucination from an Embodied-Cognitive Translatology Perspective.

    .- A Study on Chinese Acronym Prediction Based on Contextual Thematic Consistency.

    .- Learning Supportive Two-Stream Network for Audio-Visual Segmentation.

    .- Multi-exposure Driven Stable Diffusion for Shadow Removal.

    .- Human disease prediction based on symptoms using novel machine learning.

    .- CAT-LCAN: A Multimodal Physiological Signal Fusion Framework for Emotion Recognition.

    .- A novel thermal imaging and machine learning based privacy preserving framework for efficient space allocation, utilisation and management.

    .- Training Feature-Awared GPU-Memory Allocation and Management for Deep Neural Networks.

    .- TR-LDA: An Improved Potential Topic Recognition Model.

    .- Brain-inspired object domain adaptive segmentation.

    .- Task adaptive feature distribution based network for few-shot fine-grained target classification.

    .- ST TransNeXt: A Novel Pig Behavior Recognition Model.

    .- A Method for Predicting The RUL of HDDs Based on Bidirectional LSTM and Transformer.

    .- Spatio-temporal Graph Learning on Adaptive Mined Key Frames for High-performance Multi-Object Tracking.

    .- From image to the ground: Recover the ground location of vehicles from traffic cameras using neural networks.

    .- In-depth Evaluation and Analysis of Hyperspectral Unmixing Algorithms with Cognitive Models.

    .- Effective Gas Classification using Singular Spectrum Analysis and Random Forest in Electronic Nose Applications.