LEADER 05164nam 22006015 450 001 996635670403316 005 20250626164349.0 010 $a9783031781131 010 $a3031781139 024 7 $a10.1007/978-3-031-78113-1 035 $a(CKB)36813089700041 035 $a(MiAaPQ)EBC31812815 035 $a(Au-PeEL)EBL31812815 035 $a(DE-He213)978-3-031-78113-1 035 $a(EXLCZ)9936813089700041 100 $a20241204d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPattern Recognition $e27th International Conference, ICPR 2024, Kolkata, India, December 1?5, 2024, Proceedings, Part XXX /$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 (510 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15330 311 08$a9783031781124 311 08$a3031781120 327 $aDCI-Net: Remote Sensing Image-based Object Detector -- CROSS-MODAL SHIP GROUNDING: TOWARDS LARGE MODEL FOR ENHANCED FEW-SHOT LEARNING -- STNet: Small Target Detection Network for IR Imagery -- FF-Yolo: A Feature-fusion Yolo model for Small Scale FODs detection in Airport Runways -- Weakly Aligned Multi-Spectral Pedestrian Detection via Cross-Modality Differential Enhancement and Multi-Scale Spatial Alignment -- CrackUDA: Incremental Unsupervised Domain Adaptation for Improved Crack Segmentation in Civil Structures -- DS MYOLO: A Reliable Object Detector Based on SSMs for Driving Scenarios -- Robust Single-Cam Surround View Object Detection and Localization Using Memory Maps -- Exploring the Reliability of Foundation Model-Based Frontier Selection in Zero-Shot Object Goal Navigation -- Reliable Semantic Understanding for Real World Zero-shot Object Goal Navigation -- AllWeather-Net: Unified Image Enhancement for Autonomous Driving Under Adverse Weather and Low-Light Conditions -- Uni4DAL: A Unified Baseline for Multi-dataset 4D Auto-Labeling -- Dual-Attention Fusion Network with Edge and Content Guidance for Remote Sensing Images Segmentation -- Distortion Correction Sub-Network for Semantic Segmentation based on Deep Hough Transform -- MemoFlow: Modifying Explicit Motion of Inconsistency in Optical Flow -- Enhanced Brain Tumor Segmentation Using Preprocessing Techniques and 3D U-Net -- Joint Top-Down and Bottom-Up Frameworks for 3D Visual Grounding -- Anticipating Future Object Compositions without Forgetting -- SPK: Semantic and Positional Knowledge for Zero-shot Referring Expression Comprehension -- Can Language Improve Visual Features For Distinguishing Unseen Plant Diseases? -- Show Me the World in My Language: Establishing the First Baseline for Scene-Text to Scene-Text Translation -- iGrasp: An Interactive 2D-3D Framework for 6-DoF Grasp Detection -- Goal-Driven Transformer for Robot Behavior Learning from Play Data -- Adaptive Dynamic VSLAM: Refining Semantic-Geometric Fusion and Static Background Inpainting -- Hierarchical Visual Place Recognition with Semantic-guided Attention -- Dense Reconstruction and Localization in Scenes with Glass Surfaces Based on ORB-SLAM2 -- Content-Aware Feature Upsampling for Voxel-based 3D Semantic Segmentation -- Enhancing 3D Referential Grounding by Learning Coarse Spatial Relationships -- PointGADM: Geometry Acquainted Deep Model for 3D Point Cloud Analysis -- CroMA: Cross-Modal Attention for Visual Question Answering in Robotic Surgery. 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,$x1611-3349 ;$v15330 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 $a996635670403316 996 $aPattern Recognition$94309011 997 $aUNISA