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检索条件"任意字段=4th International Conference Pattern Recognition in Bioinformatics"

共 1763 条记录，以下是1-10 订阅

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pattern recognition in bioinformatics - 4th IAPR international conference, PRIB 2009, Proceedings

Pattern Recognition in Bioinformatics - 4th IAPR Internation...

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4th IAPR international conference on pattern recognition in bioinformatics, PRIB 2009

ISBN: (纸本)3642040306

the proceedings contain 38 papers. the topics discussed include: evolutionary parameters in sequence families: cold adaptation of enzymes;MProfiler: a profile-based method for DNA motif discovery;on utilizing optimal and information theoretic syntactic modeling for peptide classification;multiclass microarray gene expression analysis based on mutual dependency models;an efficient convex nonnegative network component analysis for gene regulatory network reconstruction;using higher-order dynamic Bayesian networks to model periodic data from the circadian clock of Arabidopsis thaliana;syntactic pattern recognition using finite inductive strings;evidence-based clustering of reads and taxonomic analysis of metagenomic data;and avoiding spurious feedback loops in the reconstruction of gene regulatory networks with dynamic Bayesian networks.

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4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

4th International Conference on Pattern Recognition and Arti...

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4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

ISBN: (纸本)9789819787043

the proceedings contain 69 papers. the special focus in this conference is on pattern recognition and Artificial Intelligence. the topics include: Hierarchical Attention Decoder for Solving Math Word Problems;enhancing Output Diversity Improves Conjugate Gradient-Based Adversarial Attacks;open-World Visual Reasoning by a Neuro-Symbolic Program of Zero-Shot Symbols;the Hidden Influence of Latent Feature Magnitude When Learning with Imbalanced Data;AM-SORT: Adaptable Motion Predictor with Historical Trajectory Embedding for Multi-Object Tracking;character Identifying Video Language Alignment Network for Weakly-Supervised Video-Subtitle Moment Retrieval;spiral Patch Exemplar-Based Inpainting of 3D Colored Meshes;BEVFormer’s Plugin: Integrating Historical Detection Data, BEV-Level Information, Time Information, and Depth Information;adjustable Visual Appearance for Generalizable Novel View Synthesis;flexible Video Matting With Temporally Coherent Trimaps Generation;adversarial Augmentation Training Makes Action recognition Models More Robust to Realistic Video Distribution Shifts;egocentric View Hand Action recognition by Leveraging Hand Surface and Hand Grasp Type;visual Concept Networks: A Graph-Based Approach to Detecting Anomalous Data in Deep Neural Networks;contrastive Language-Entity Pre-training for Richer Knowledge Graph Embedding;Fine-Tuning Pre-trained Model with Prototype Learning for OOD Detection;prototype-Guided Contrastive Knowledge Graph Representation Learning for Diagnosis Prediction;stop Overkilling Simple Tasks with Black-Box Models, Use More Transparent Models Instead;feature-Based Explainable Reinforcement Learning in Environments with Multiple Sources of Risk;probing Network Decisions: Capturing Uncertainties and Unveiling Vulnerabilities Without Label Information;enhancing Robustness of Over-Parameterized Models via Feature Reweighting Using Logit-Wise Mixup;language-Aware Non-autoregressive Khmer Textline recognition;ATA: Attentive Text Augment

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4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

4th International Conference on Pattern Recognition and Arti...

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4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

ISBN: (纸本)9789819787012

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4th international conference on Intelligent Systems and pattern recognition, ISPR 2024

4th International Conference on Intelligent Systems and Patt...

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4th international conference on Intelligent Systems and pattern recognition, ISPR 2024

ISBN: (纸本)9783031821554

the proceedings contain 77 papers. the special focus in this conference is on Intelligent Systems and pattern recognition. the topics include: Tunisian Sign Language recognition and Translation Using Deep Learning;Beyond Spatial: A Wavelet Fusion-Based Deep Learning CAD for Skin Cancer Diagnosis;integrating Machine Learning and Deep Learning Techniques for Enhanced Historical Script Classification;efficiency Meets Resilience: Accelerating Object Detection in Embedded Environments through Compressive Sensing;PMoET: Going Wider than Deeper Using the Parallel Mixture of Experts Transformer for 3D Hand Gesture recognition;Enhancing Forest Fire Classification with Feature Selection and Machine Learning Based on PRISMA Hyperspectral Data;semantic Segmentation of Unmanned Aerial Vehicle Remote Sensing Images Using SegFormer;handcrafted and Deep Features for Synthetic Data Generation in Offline Handwritten Signature Verification;refining U-Net Architecture through Genetic Algorithms for Improved Skin Lesion Image Segmentation;An RNN-LSTM Approach for Algerian Accent Identification;ensemble Methods for Predicting Cyanobacteria’s Potential Toxicity in Water Dams;cross-Organ Investigation of Tumor Histological Features Similarities Using Transfer Learning: A Case Study on Breast and Colorectal Tumors;behavior-Based Insider threat Detection Using a Deep Neural Network;holistic Ontology Alignment Using Ontologies Embeddings;learning Different Separations in Branch and Cut: A Survey;Cancer Classification in Breast Imaging via Enhanced CNN Deep Learning Architecture;X-Ray Insights: A Siamese with CNN and Spatial Attention Network for Innovative Person Identification;hybrid Wiener Filter and Sharpening Filter for Image De-blurring;feature Extraction and Dimensionality Reduction to Evaluate Decision Tree Ensembles for Diabetic Retinopathy Detection;artificial Intelligence-Based on Automatic Detection of Diabetic Eye Diseases : A Systematic Review;automated Breast Cancer Detection: A

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4th international conference on Intelligent Systems and pattern recognition, ISPR 2024

4th International Conference on Intelligent Systems and Patt...

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4th international conference on Intelligent Systems and pattern recognition, ISPR 2024

ISBN: (纸本)9783031821523

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4th international conference on Intelligent Systems and pattern recognition, ISPR 2024

4th International Conference on Intelligent Systems and Patt...

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4th international conference on Intelligent Systems and pattern recognition, ISPR 2024

ISBN: (纸本)9783031821493

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BEVFormer’s Plugin: Integrating Historical Detection Data, BEV-Level Information, Time Information, and Depth Information 4th

BEVFormer’s Plugin: Integrating Historical Detection Data, ...

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4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

作者： Pan, Zeen Tong, Zongyang Dong, Yuhan Shenzhen International Graduate School Tsinghua University Shenzhen China

ISBN: (纸本)9789819787012

this paper presents a novel approach to camera-based 3D object detection, a critical task in autonomous driving systems. We propose a method that leverages historical information and introduces a plug-and-play characteristic during training. Our approach builds upon existing methods by extending the concept of historical feature augmentation and fully exploiting historical information, significantly enhancing detection performance. We also introduce an auxiliary loss operating at the Bird’s Eye View (BEV) level, which meticulously cultivates the model’s environmental cognition. To address the temporal dimension’s inherent lack in the BEV framework, we incorporate a temporal embedding module into the BEV feature amalgamation. Our method elevates the detection paradigm by harnessing historical and temporal information and integrating a BEV-level supervisory framework. We validate our approach through extensive experiments, demonstrating its superiority in real-world scenarios and potential for applications in autonomous driving, video surveillance, and intelligent transportation systems. © the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Driver licensing

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Generate Vector Graphics of Fine-grained pattern based on the Xception Edge Detection 4

Generate Vector Graphics of Fine-grained Pattern based on th...

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4th international conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Chen, Anqi Chen, Hao Peng, Yicui Hu, Jinrong Deng, Linjie Wen, Xiang Wang, Xin Chengdu Technological University Chengdu China Chengdu University of Information Technology Chengdu China Industry Research Institute Chengdu China University at Buffalo United States

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

the innovative generation of vector graphics with fine-grained images using Artificial Intelligence has become an important task in edge extraction. In this paper, we take Qiang embroidery image as an example due to its containing fine-grained edges, which is more suitable for the study of image processing and pattern recognition. We firstly adopt appropriate pre-processing methods, improved adaptive median filtering (IAMF) for the image to reduce image noise. then, the Xception based on convolutional neural networks is used for edge detection and extraction. Results show that Qiang embroidery images, after denoising and edge extraction, can be clearly identified the shape characteristics of the images. Based on this approach, it can be converted into vector graphics for digital preservation and further artistic reinterpretation. the use of the Xception effectively addresses Qiang embroidery extraction in two-dimensional vector images, offering a practical reference for preserving related intangible cultural heritage. © 2025 SPIE.

关键词： Median filters

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A Synthetic Benchmarking Pipeline to Compare Camera Calibration Algorithms 27th

A Synthetic Benchmarking Pipeline to Compare Camera Calibra...

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27th international conference on pattern recognition, ICPR 2024

作者： Ray, Lala Shakti Swarup Zhou, Bo Krupp, Lars Suh, Sungho Lukowicz, Paul German Research Center for Artificial Intelligence Kaiserslautern Germany RPTU Kaiserslautern-Landau Kaiserslautern Germany

ISBN: (纸本)9783031781247

Accurate camera calibration is crucial for various computer vision applications. However, measuring calibration accuracy in the real world is challenging due to the lack of datasets with ground truth to evaluate them. In this paper, we present SynthCal, a synthetic camera calibration benchmarking pipeline that generates images of calibration patterns to measure and enable accurate quantification of calibration algorithm performance in camera parameter estimation. We present a SynthCal-generated calibration dataset with four common patterns, two camera types, and two environments with varying view, distortion, lighting, and noise levels for both monocular and multi-camera systems. the dataset evaluates both single and multi-view calibration algorithms by measuring re-projection and root-mean-square errors for identical patterns and camera settings. Additionally, we analyze the significance of different patterns using different calibration configurations. the experimental results demonstrate the effectiveness of SynthCal in evaluating various calibration algorithms and patterns. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： benchmarking camera calibration pattern recognition synthetic dataset

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Conversation Activity recognition Using Interaction Video Sequences in Pedestrian Groups 27th

Conversation Activity Recognition Using Interaction Video Se...

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27th international conference on pattern recognition, ICPR 2024

作者： Ganaha, Wataru Ozaki, Takumi Inoue, Michiko Nishiyama, Masashi Graduate School of Engineering Tottori University 101 Minami 4-chome Koyama-cho Tottori680-8550 Japan

ISBN: (纸本)9783031783401

We introduce a method for recognizing conversation activity in a group of people walking outdoors using a color video sequence acquired from a camera. Many methods have been developed to recognize whether people are walking together or talking together in a color video sequence. However, a method has yet to be proposed to recognize conversation activity in a pedestrian group walking outdoors. In this paper, we design a feature extraction approach for conversation activity recognition using physical body interactions caused by pedestrians’ conversations. Our method generates an interaction video sequence in a virtual space using a temporal posture signal and a temporal walking position signal that represent pedestrians’ body interactions. Our method uses the interaction video sequence as an informative and visible feature to determine a conversation activity label. the experimental results showed that our interaction video sequence recognized conversation activity more accurately than alternative techniques that use the appearance of the body regions of a pedestrian group or time-series changes of the posture and walking position among pedestrians. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Color computer graphics

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