LEADER 01184nam a2200301 i 4500 001 991003680909707536 008 070108s2003 miua b 001 0 eng d 020 $a0870311085 035 $ab1373457x-39ule_inst 040 $aDip.to Ingegneria dell'Innovazione$beng 082 $a624.18341 245 00$aLarge-scale structural testing /$ceditors, Mohsen A. Issa and Y.L. Mo 246 3 $aLarge scale structural testing 260 $aFarmington Hills, Mich. :$bAmerican Concrete Institute,$cc2003 300 $avi, 372 p. :$bill. ;$c23 cm. 440 $aACI international SP ;$v211 504 $aIncludes bibliographical references and indexes 650 4$aConcrete construction$xTesting 650 4$aReinforced concrete construction$xTesting 700 1 $aIssa, Mohsen A. 700 1 $aMo, Y. L. 710 2 $aAmerican Concrete Institute 907 $a.b1373457x$b28-01-14$c06-06-08 912 $a991003680909707536 945 $aLE026 624.18341 ISS 01.01 2003$g1$i2026000041391$lle026$op$pE103.49$q-$rl$s- $t4$u0$v0$w0$x0$y.i14770647$z06-06-08 996 $aLarge-scale structural testing$91227084 997 $aUNISALENTO 998 $ale026$b08-01-07$cm$da $e-$feng$gmiu$h0$i0 LEADER 04989nam 22006135 450 001 996635663603316 005 20250626163937.0 010 $a9783031781223 010 $a3031781228 024 7 $a10.1007/978-3-031-78122-3 035 $a(MiAaPQ)EBC31815221 035 $a(Au-PeEL)EBL31815221 035 $a(CKB)36822886700041 035 $a(DE-He213)978-3-031-78122-3 035 $a(OCoLC)1477224951 035 $a(EXLCZ)9936822886700041 100 $a20241204d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPattern Recognition $e27th International Conference, ICPR 2024, Kolkata, India, December 1?5, 2024, Proceedings, Part III /$fedited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (511 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15303 311 08$a9783031781216 311 08$a303178121X 327 $aDeep 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. 330 $aThe multi-volume set of LNCS books with volume numbers 15301-15333 constitutes the refereed proceedings of the 27th International Conference on Pattern Recognition, ICPR 2024, held in Kolkata, India, during December 1?5, 2024. The 963 papers presented in these proceedings were carefully reviewed and selected from a total of 2106 submissions. They deal with topics such as Pattern Recognition; Artificial Intelligence; Machine Learning; Computer Vision; Robot Vision; Machine Vision; Image Processing; Speech Processing; Signal Processing; Video Processing; Biometrics; Human-Computer Interaction (HCI); Document Analysis; Document Recognition; Biomedical Imaging; Bioinformatics. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v15303 606 $aComputer vision 606 $aMachine learning 606 $aComputer Vision 606 $aMachine Learning 615 0$aComputer vision. 615 0$aMachine learning. 615 14$aComputer Vision. 615 24$aMachine Learning. 676 $a006.37 700 $aAntonacopoulos$b Apostolos$0885419 701 $aChaudhuri$b Subhasis$0846530 701 $aChellappa$b Rama$0491442 701 $aLiu$b Cheng-Lin$0861045 701 $aBhattacharya$b Saumik$01782600 701 $aPal$b Umapada$01782601 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996635663603316 996 $aPattern Recognition$94309011 997 $aUNISA