Muutke küpsiste eelistusi

E-raamat: Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part IV

Edited by , Edited by , Edited by , Edited by , Edited by , Edited by , Edited by , Edited by
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 80,26 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part IVSuurem pilt
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

This 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024.
The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.

Contextual Feature-Based Medical Visual Question Answering Aided by
Learnable Matrix.- ImgQuant: Towards adversarial defense with robust boundary
via dual-image quantization.- Swelling-ViT: Rethink Data-efficient Vision
Transformer from Locality.- Target-Specific Domain Adaptation via
Geometry-Correlation Prediction for Point Cloud.- Dual-stream Network of
Vision Mamba and CNN with Auto-scaling for Remote Sensing Image
Segmentation.- PRM: A Pixel-Region-Matching Approach for Fast Video Object
Segmentation.- A Novel Combined GAN for Defects Generation using Masking
Mechanisms.- Semi-supervised lightweight fabric defect detection.-
Semi-adaptive Synergetic Two-way Pseudoinverse Learning System.- Invariant
Risk Minimization Augmentation for Graph Contrastive Learning.- Enhancing
Fast Adversarial Training with Learnable Adversarial Perturbations.-
DTAFORMER: Directional Time Attention Transformer For Long-Term Series
Forecasting.- Unpaired Multi-scenario Sketch Synthesis via Texture
Enhancement.- ISO-VTON: Fine-Grained Style-Local Flows with Dual
Cross-Attention for Immersive Outfitting.- Near-surface Air Temperature
Inversion Study Based on U-Net Family with Multi-source Data.- Relation
Detection with Transformers for Panoptic Scene Graph Generation.- WEDNet: A
Wavelet Enhanced Detail Network for Low-Light Image Enhancement.-
Textureness-Aware Neural Network for Edge Detection.- Enhancing the
Transferability and Stealth of Deepfake Detection Attacks Through Latent
Diffusion Models.- Backdoor Richer Watermarks using Dynamic Mask Covering for
Dual Identity Verification.- Pedestrian Trajectory Prediction using
Spatio-Temporal VAE.- Real-Time DEtection TRansformer with Bi-Level Routing
Attention.- NFP-UNet: Deep Learning Estimation of Placeable Areas for 2D
Irregular Packing.- Advancements in Photorealistic Style Translation with a
Hybrid  Generative Adversarial Network.- Transformer Image Quality Assessment
Based on Multi-Directional Feature Extraction.- MRGAN: LightWeight Monaural
Speech Enhancement using GAN Network.- Data augmentation guided Decouple
Knowledge Distillation for low-resolution fine-grained image classification.-
GAN-Diffusion Relay Model: Advancing Semantic Image Synthesis.- Virtual
Student Distribution Knowledge Distillation for Long-tailed Recognition.-
Open-Vocabulary Instance Segmentation-Boundary IS-Goal.- 3DLaneFormer:
End-to-End 3D Lane Detection with Voxel Descriptors.- More Like Real World
Game Challenge for Partially Observable Multi-Agent Cooperation.-
Centroid-centered Modeling for Efficient Vision Transformer Pre-training.-
SpectralSpatial Blockwise Masked Transformer With Contrastive Multi-View
Learning for Hyperspectral Image Classification.- Local reactivation for
communication efficient federated learning based on sparse gradient deviation.
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
Püsilink: https://www.kriso.ee/db/97898197850566e.html