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ReID-DeePNet: A Hybrid Deep Learning System for Person Re-Identification
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Outgoing claims: the papers this work cites, builds on, or argues with.
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A novel deep model with multi-loss and efficient training for person re-identification
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Multi-level attention model for person re-identification
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Deep Belief Network Integrating Improved Kernel-Based Extreme Learning Machine for Network Intrusion Detection
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Real-World Person Re-Identification via Super-Resolution and Semi-Supervised Methods
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DeepReID: Deep Filter Pairing Neural Network for Person Re-identification
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Person re-identification by Local Maximal Occurrence representation and metric learning
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Learning Deep Context-Aware Features over Body and Latent Parts for Person Re-identification
inferredcites →https://doi.org/10.1109/cvpr.2018.00129openalex-snapshot
Mask-Guided Contrastive Attention Model for Person Re-identification
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Clothes-Changing Person Re-identification with RGB Modality Only
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NFormer: Robust Person Re-identification with Neighbor Transformer
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Learning with Twin Noisy Labels for Visible-Infrared Person Re-Identification
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Deeply-Learned Part-Aligned Representations for Person Re-identification
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Towards Discriminative Representation Learning for Unsupervised Person Re-identification
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Deep Self-Paced Learning for Semi-Supervised Person Re-Identification Using Multi-View Self-Paced Clustering
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The P-DESTRE: A Fully Annotated Dataset for Pedestrian Detection, Tracking, and Short/Long-Term Re-Identification From Aerial Devices
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End-to-End Domain Adaptive Attention Network for Cross-Domain Person Re-Identification
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/tpami.2021.3054775openalex-snapshot
Deep Learning for Person Re-Identification: A Survey and Outlook
inferredcites →https://doi.org/10.1117/12.2587946openalex-snapshot
A study of person re-identification design characteristics for aerial data
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Deep learning-based video analysis pipeline for person detection and re-identification in aerial imagery
inferredcites →https://doi.org/10.1126/science.1127647openalex-snapshot
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Harmonious Multi-branch Network for Person Re-identification with Harder Triplet Loss
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Horizontal Pyramid Matching for Person Re-Identification
inferredcites →https://doi.org/10.3390/s19092080openalex-snapshot
A Dynamic Part-Attention Model for Person Re-Identification
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A Spatio-Temporal Descriptor Based on 3D-Gradients
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Multi-task model with attribute-specific heads for person re-identification
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inferred← citeshttps://doi.org/10.1007/s12652-025-04974-4openalex-snapshot
HyDeepIDF-Net: Hybrid Deep ID FaceNet for Person Re-Identification
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Spatio-temporal information mining and fusion feature-guided modal alignment for video-based visible-infrared person re-identification
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Neighboring-Part Dependency Mining and Feature Fusion Network for Person Re-Identification
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Dual-Backbone Feature Fusion of EfficientNet and ResNet for Person Identification from Drone-Captured Silhouettes
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Lightweight Person Re-identification Network Based on Fine-grained Feature Localization
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Person Re-Identification with Face Detection Using Deep Residual Network
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ATTL: Adaptive Thresholding Triplet Loss for Robust Person Re-identification
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A Machine Learning Model for the Prediction of Heart Attack Risk in High-Risk Patients Utilizing Real-World Data
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Person Re-Identification Network Based on Edge-Enhanced Feature Extraction and Inter-Part Relationship Modeling
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The Role of International Research Collaboration and Faculty Related Factors in Publication Citations: Evidence from Lebanon
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A Multimodule Collaborative Framework for Unsupervised Visible–Infrared Person Re-Identification with Channel Enhancement Modality
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