Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Heritage Preservation : A Computational Approach / / edited by Bhabatosh Chanda, Subhasis Chaudhuri, Santanu Chaudhury
| Heritage Preservation : A Computational Approach / / edited by Bhabatosh Chanda, Subhasis Chaudhuri, Santanu Chaudhury |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 345 p.) |
| Disciplina | 005.7 |
| Soggetto topico |
Application software
Optical data processing Information Systems Applications (incl. Internet) Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 981-10-7221-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Digital System for Heritage Preservation -- Chapter 2. Signal and Image Processing -- Chapter 3. Audio and Video Processing -- Chapter 4. Image and Video Database -- Chapter 5. Architectural Modelling and Visualization. |
| Record Nr. | UNINA-9910299305703321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXXII / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXXII / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (465 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031781254
3031781252 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Pixel Embedding for Fractional Interpolation in Video Coding -- Scene Text Image Super-Resolution with CLIP Prior Guidance -- A Coverless Steganography of Face Privacy Protection with Diffusion Models -- CLIP-AGIQA: Boosting the Performance of AI-Generated Image Quality Assessment with CLIP -- CoDeiT: Contrastive Data-efficient Transformers for Deepfake Detection -- A Lightweight and High-Fidelity Model for Generalized Audio-Driven 3D Talking Face Synthesis -- Illuminating the Dark: Unpaired Retinex and FFT-Based Low-Light Image Enhancement -- PSTNet: A Progressive Sparse Transformer Network for Image Deraining -- Frequency Modulated Deformable Transformer for Underwater Image Enhancement -- Probing Attention-Driven Normalizing Flow Network for Low-Light Image Enhancement -- A Novel Encoder-Decoder Network with Multi-domain Information Fusion for Video Deblurring -- Self-Distilled Dual-Network with Pixel Screening Loss for Blind Image Deblurring -- Complementary Dual-Branch Network for Space-Time Video Super-Resolution -- SINGLE-IMAGE DRIVEN 3D VIEWPOINT TRAINING DATA AUGMENTATION FOR EFFECTIVE LABEL RECOGNITION -- Lightweight Single Image Super-Resolution Network Integrating CNN and Transformer -- A Synthetic Benchmarking Pipeline to Compare Camera Calibration Algorithms -- Arbitrary Clothing Style Transfer Based on Attention Mechanism -- Approximate Cuboidization of an Orthogonal Polyhedron: A Combinatorial Approach -- Enhancing Multi-Exposure High Dynamic Range Imaging with Overlapped Codebook for Improved Representation Learning -- Deformable Multi-Scale Network for Snow Removal in Video -- Fast Orthogonal Matching Pursuit through Successive Regression -- MPGTSRN: Scene Text Image Super-Resolution Guided by Multiple Visual-Semantic Prompts -- Connecting the Dots: Isolated Trails of Detected Narrow Rivers in Multispectral Images -- Peel and Pool: The Path to Mandala Perfection -- MCANet: Multimodal Caption Aware Training-free Video Anomaly Detection via Large Language Model -- 2by2: Weakly-Supervised Learning for Global Action Segmentation -- MDFIDNet: Multi Domain Feature Integration Denoising Network -- Dynamic Resolution Guidance for Facial Expression Recognition. |
| Record Nr. | UNINA-9910983486203321 |
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part IV / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part IV / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (0 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031781285
3031781287 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | DeepEMD: A Transformer-based Fast Estimation of the Earth Mover’s Distance -- Equivariant Neural Networks for TEM Virus Images Improves Data Efficiency -- AI Based Story Generation -- Deep learning models for inference on compressed signals with known or unknown measurement matrix -- Training point-based deep learning networks for forest segmentation with synthetic data -- Brain Age Estimation using Self-attention based Convolutional Neural Network -- IFSENet : Harnessing Sparse Iterations for Interactive Few-shot Segmentation Excellence -- Interpretable Deep Graph-level Clustering: A Prototype-based Approach -- A Saliency-Aware NR-IQA Method by Fusing Distortion Class Information -- A Guided Input Sampling-based Perturbative Approach for Explainable AI in Image-based Application -- Multi-target Attention Dispersion Adversarial Attack against Aerial Object Detector -- Mask-TS Net: Mask Temperature Scaling Uncertainty Calibration for Polyp Segmentation -- Label-expanded Feature Debiasing for Single Domain Generalization -- Infrared and Visible Image Fusion Based on CNN and Transformer Cross-Interaction with Semantic Modulations -- Mining Long Short-Term Evolution Patterns for Temporal Knowledge Graph Reasoning -- Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical Imaging -- A Weighted Discrete Wavelet Transform-based Capsule Network for Malware Classification -- Data-driven Spatiotemporal Aware Graph Hybrid-hop Transformer Network for Traffic Flow Forecasting -- Automatic Diagnosis Model of Gastrointestinal Diseases Based on Tongue Images -- TinyConv-PVT: A Deeper Fusion Model of CNN and Transformer for Tiny Dataset -- SCAD-Net: Spatial-Channel Attention and Depth-map Analysis Network for Face Anti-Spoofing -- Next Generation Loss Function for Image Classification -- NAOL: NeRF-Assisted Omnidirectional Localization -- EdgeConvFormer: an unsupervised anomaly detection method for multivariate time series -- Lighten CARAFE: Dynamic Lightweight Upsampling with Guided Reassemble Kernels -- Hand over face gesture classification with feature driven vision transformer and supervised contrastive learning -- TabSeq: A Framework for Deep Learning on Tabular Data via Sequential Ordering -- GraFix: A Graph Transformer with Fixed Attention based on the WL Kernel -- Multi-Modal Deep Emotion-Cause Pair Extraction for Video Corpus. |
| Record Nr. | UNINA-9910983299003321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XIX / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XIX / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (526 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031784958
3031784952 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983086103321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXV / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXV / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (470 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031783890
3031783891 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- President's Address -- Preface -- Organization -- Contents - Part XXV -- A Novel Loss for Contrastive Deep Supervision -- 1 Introduction -- 2 Related Work -- 2.1 Contrastive Learning -- 2.2 Supervised Contrastive Learning -- 2.3 Deep Supervision -- 3 Method -- 3.1 NCDS Framework -- 3.2 Analysis of . -- 3.3 The Novel Loss -- 4 Experiment -- 5 Conclusion -- References -- Multi-Task Interaction Network Based on a Cross-Attention Fusion Mechanism for Offline Signature Verification -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Network Architecture -- 3.2 Contrastive Interaction Module -- 3.3 Self-Channel Interaction Module -- 4 Experiments -- 4.1 Ablation Studies -- 4.2 Comparison with State of the Art -- 4.3 Cross-Language Test -- 4.4 Visualization -- 5 Conclusion -- References -- Functional Tensor Decompositions for Physics-Informed Neural Networks -- 1 Introduction -- 2 Theoretical Background -- 2.1 Universal Approximation Theorem -- 2.2 Physics-Informed Neural Networks -- 2.3 Functional Tensor Decompositions for PINNs -- 3 Experiments -- 4 Discussion and Conclusions -- References -- Squeeze and Hypercomplex Networks on Leaf Disease Detection -- 1 Introduction -- 2 Literature Reviews -- 2.1 Rice Leaf Diseases Detection -- 2.2 Wheat Leaf Diseases Detection -- 2.3 Corn Leaf Diseases Detection -- 2.4 New Plant Leaf Diseases Data -- 3 Background Works -- 3.1 Residual 1D Convolutional Networks -- 3.2 Quaternion Convolution Networks -- 3.3 Parameterized Hypercomplex Multiplication Layer -- 3.4 Squeeze-and-Excitation Network -- 4 Proposed Squeeze-and-Hypercomplex Network -- 5 EXPERIMENTAL RESULTS -- 5.1 Dataset Description -- 5.2 Method -- 5.3 Result Analysis -- 5.4 Comparison with the Literature -- 5.5 Ablation Study -- 6 Conclusion -- References -- Mangoes Ripeness Grading: Vision Based Approach -- 1 Introduction.
2 Materials and Methods -- 2.1 Data Sets and Experimentation Setup -- 2.2 Data Augmentation -- 2.3 Proposed Methodology -- 3 Results and Discussion -- 4 Conclusion -- References -- FedRewind: Rewinding Continual Model Exchange for Decentralized Federated Learning -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 The Rewind Strategy -- 4 Results -- 4.1 Federated Learning Performance -- 4.2 Continual Federated Learning -- 5 Conclusion -- References -- On the Relationship Between Double Descent of CNNs and Shape/Texture Bias Under Learning Process -- 1 Introduction -- 2 Related Work -- 2.1 Double descent -- 2.2 CNN for image understanding -- 3 Correlation analysis framework of double descent and shape/texture bias -- 3.1 How to observe double descent -- 3.2 Phases of learning curve with double descent -- 3.3 Quantifying the shape/texture bias of the model -- 4 Experiments -- 4.1 Nakkiran's setting -- 4.2 Ablation studies and analyses -- 4.3 Layer-wise analyses and visualization -- 5 Discussion -- 6 Conclusion -- References -- Cystic Adenocarcinoma Segmentation Based on Multi-frequency and Multi-scale SimAM Attention -- 1 Introduction -- 2 Related Works -- 2.1 Model Architecture -- 2.2 Attention Mechanisms -- 3 Methods -- 3.1 Model Architecture -- 3.2 Fusion of Shallow Features And Deep Semantic Features Unit -- 3.3 Multi-Frequency in Multi-Scale SimAM Attention -- 4 Experiments -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Experiment Settings -- 4.4 Comparison With SOTA Models -- 4.5 Ablation Study On LungSSFNet -- 5 Conclusion -- References -- MSDNet: A Multi-scale Dense Network for Chip Surface Defect Segmentation -- 1 Introduction -- 2 Related Works -- 2.1 Defect Classification -- 2.2 Defect Detection -- 2.3 Defect Segmentation -- 3 Method -- 3.1 Architecture -- 3.2 Multi-scale Convolution Module -- 3.3 Node Module -- 3.4 Attention Module. 3.5 Loss Function -- 4 Experiments -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Experimental Results -- 4.4 Ablation Study -- 5 Conclusion -- References -- Task Oriented Image Quality Assessment for Synthesized Images -- 1 Introduction -- 2 Related Work -- 2.1 Reference-guided image synthesis (RIS) -- 2.2 Image Quality Assessment(IQA) -- 3 Methodology -- 3.1 Style Level Interpolation for Data Preparation -- 3.2 Learning-based Quality Score Estimation -- 3.3 Training Objective -- 4 EXPERIMENT -- 4.1 Dataset -- 4.2 Protocol and Evalution criteria -- 4.3 Performance Evalution -- 4.4 CONCLUSION -- References -- SANGAM: Synergizing Local and Global Analysis for Simultaneous WBC Classification and Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 WBC Segmentation -- 2.2 WBC Classification -- 3 Proposed System -- 3.1 WBC Segmentation -- 3.2 WBC Classification -- 3.3 Refined WBC Segmentation -- 4 Experimental Results -- 4.1 Experimental settings -- 4.2 Implementation details -- 4.3 Training and Testing settings -- 4.4 Comparative WBC Segmentation Performance -- 4.5 Comparative WBC Classification Performance -- 4.6 Ablation study -- 5 Conclusion -- References -- MeDiANet: A Lightweight Network for Large-scale Multi-disease Classification of Multi-modal Medical Images Using Dilated Convolution and Attention Network -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Residual Block -- 3.2 Multi Dilated residual block -- 3.3 Dilated Residual Attention Block -- 3.4 MeDiANet -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Evaluation Metrics -- 5 Results & -- Discussions -- 6 Conclusion -- References -- A Data Augmentation Approach for Well Log Interpretation -- 1 Introduction -- 2 Related Works -- 2.1 Data Augmentation -- 2.2 Time-frequency Augmentation -- 3 Method -- 3.1 Time-domain Method. 3.2 Frequency-domain Method -- 4 Experiment -- 4.1 Dataset -- 4.2 Experimental Setting -- 4.3 Experimental Results -- 5 Conclusion -- References -- TSAK: Two-Stage Semantic-Aware Knowledge Distillation for Efficient Wearable Modality and Model Optimization in Manufacturing Lines -- 1 Introduction -- 2 Related Work -- 3 Apparatus and Dataset -- 4 Knowledge Distillation Approach -- 5 Result and Discussion -- 6 Conclusion -- References -- ArtNeRF: A Stylized Neural Field for 3D-Aware Artistic Face Synthesis -- 1 Introduction -- 2 Related works -- 2.1 Style Transfer with 2D GAN -- 2.2 3D-aware Image Synthesis -- 3 Method -- 3.1 Preliminaries -- 3.2 Self-supervised Style Encoder -- 3.3 Conditional Generative Radiance Field -- 3.4 Neural Rendering Module -- 3.5 Triple Discriminator Network -- 3.6 Loss Functions -- 4 Experiments -- 4.1 Comparisons -- 4.2 Ablation Study -- 5 Conclusion -- References -- Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting -- 1 Introduction -- 2 Related Works -- 2.1 Deterministic reaction synthesis -- 2.2 Multiple Reaction Generation -- 3 Proposed Method -- 3.1 Problem definition -- 3.2 Facial Reaction Compression -- 3.3 Latent Behavior Diffusion -- 4 Experiments -- 4.1 Evaluation setup -- 4.2 Evaluation metric -- 4.3 Results -- 4.4 Ablation Study -- 5 Conclusion -- References -- CFTS-GAN: Continual Few-Shot Teacher Student for Generative Adversarial Networks -- 1 Introduction -- 2 Literature Review -- 3 Method -- 3.1 Continual Few-Shot GAN -- 3.2 Cross Domain Consistency Loss -- 3.3 Teacher Student Model -- 4 Experiments -- 4.1 Qualitative Results -- 4.2 Quantitative Results -- 4.3 Ablation Study -- 5 Conclusion -- References -- T2R-GAN: A CGAN-based model for rural thematic road extraction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Overview of T2R-GAN. 3.2 ELAU-Net Generator and PatchGAN Discriminator -- 3.3 Bilateral Hinge Loss -- 4 Experiment -- 4.1 Experimental Setting -- 5 Results -- 6 Conclusion -- References -- d-Sketch: Improving Visual Fidelity of Sketch-to-Image Translation with Pretrained Latent Diffusion Models without Retraining -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Preliminaries -- 3.2 Latent Code Translation Network (LCTN) -- 4 Experiments -- 5 Conclusions -- References -- Semantically Consistent Person Image Generation -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Coarse Generation Network -- 3.2 Data-Driven Refinement Strategy -- 3.3 Appearance Attribute Transfer and Rendering -- 4 Experimental Setup -- 5 Results -- 6 Ablation Study -- 7 Limitations -- 8 Conclusions -- References -- GM-GAN: Geometric Generative Models Based on Morphological Equivariant PDEs and GANs -- 1 Introduction -- 2 Equivariance and homogeneous spaces on Riemannian manifolds -- 3 Group morphological convolutions and PDEs -- 4 Morphological equivariant PDEs for generative models -- 4.1 Morphological PDE-based layers -- 4.2 PDE model design -- 4.3 Architecture of morphological equivariant PDEs based on GAN -- 5 Numerical experiments -- 6 Conclusion and perspectives -- References -- NR-CION: Non-rigid Consistent Image Composition Via Diffusion Model -- 1 Introduction -- 2 Related work -- 2.1 Text-based image editing -- 2.2 Image composition -- 2.3 Image inversion -- 3 Preliminary -- 3.1 Latent diffusion model -- 3.2 Classifier free guidance -- 3.3 Attention mechanism -- 4 Method -- 4.1 Image inversion -- 4.2 Non-rigid foreground object generation and mask generation -- 4.3 Image composition -- 5 Experiments -- 5.1 Implementation details and benchmark -- 5.2 Compared with previous methods -- 5.3 Ablation study -- 6 Limitation and future work -- 7 Summary -- References. Neighborhood Feature Enhancement Flow Diffusion Model for Point Cloud Generation. |
| Record Nr. | UNINA-9910983357503321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XII / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XII / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (511 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031781988
3031781988 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983377603321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part III / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part III / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (511 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031781223
3031781228 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Deep Multi-order Context-aware Kernel Network for Multi-label Classification -- Classifier Enhanced Deep Learning Model for Erythroblast Differentiation with Limited Data -- PiExtract: An End-to-End Data Extraction pipeline for Pie-Charts -- Machine Learning Solutions for Predicting Bankruptcy in Indian Firms -- Efficient Object Detection via Fine-grained Regularization with Global Initialization -- On Trace of PGD-Like Adversarial Attacks -- CAB-KWS: Contrastive Augmentation: An Unsupervised Learning Approach for Keyword Spotting in Speech Technology -- Deep Learning in Automated Worm Identification and Tracking for C. Elegan Mating Behaviour Analysis -- Interactive-Time Text-Guided Editing of 3D Face -- Unlearning Vision Transformers without Retaining Data via Low-Rank Decompositions -- gWaveNet: Classification of Gravity Waves from Noisy Satellite Data using Custom Kernel Integrated Deep Learning Method -- Neural-Code PIFu: High-Fidelity Single Image 3D Human Reconstruction via Neural Code Integration -- Sea-ShipNet: Detect Any Ship in SAR Images -- Semantic Correlation Adaptation for Union-Set Multi-Label Image Recognition -- FedSC: Federated Generalized Face Anti-Spoofing via Shuffled Codebook -- LoHoSC: Low Order High Order Style Consistency for Syn-to-Real Domain Generalized Semantic Segmentation -- Incorporating Spatial Locality into Self-Attention for Training Vision Transformer on Small-Scale Datasets -- Cross-Domain Calibration and Boundary Denoising Network for Weakly Supervised Semantic Segmentation -- EFLLD-NET: Enhancing Few-Shot Learning With Local Descriptors -- Using Multiscale Information for Improved Optimization-based Image Attribution -- Split-DNN Computing for Video Analytics -- Task-Aware Local Descriptors Reconstruction Network for Few-Shot Find-Grained Image Classification -- TRIGS: Trojan Identification from Gradient-based Signatures -- Multifaceted Anchor Nodes Attack on Graph Neural Networks: A Budget-efficient Approach -- Causal Attentive Group Recommendation -- E2DAS: An Efficient Equivariant Dynamic Aggregation Saliency Model for Omnidirectional Images -- FewConv: Efficient variant convolution for few-shot image generation -- FixPix: Fixing Bad Pixels using Deep Learning -- Real-world Coarse to Fine-Grained Source-Free Multidomain Adaptation. |
| Record Nr. | UNINA-9910983073403321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXVI / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXVI / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (495 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031783951
3031783956 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983328903321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XIII / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XIII / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (504 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031782015
3031782011 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983042503321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXIV / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
| Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXIV / / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal |
| Autore | Antonacopoulos Apostolos |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (502 pages) |
| Disciplina | 006.37 |
| Altri autori (Persone) |
ChaudhuriSubhasis
ChellappaRama LiuCheng-Lin BhattacharyaSaumik PalUmapada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Machine learning Computer Vision Machine Learning |
| ISBN |
9783031783838
3031783832 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983353603321 |
|
Antonacopoulos Apostolos
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
