Reference health

Feature Distillation Siamese Networks for Object Tracking

https://doi.org/10.2139/ssrn.4194603
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20/20 checkable references clean · checked 2026-08-06

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

52 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 20 checked references that resolve
resolves10.1109/TNNLS.2018.2876865
Object Detection With Deep Learning: A Review
resolves10.1007/s11265-020-01596-1
Deep Model Compression and Architecture Optimization for Embedded Systems: A Survey
resolves10.1109/TPAMI.2014.2345390
High-Speed Tracking with Kernelized Correlation Filters
resolves10.1109/TPAMI.2016.2609928
Discriminative Scale Space Tracking
resolves10.1016/j.asoc.2018.07.049
Collaborative model based UAV tracking via local kernel feature
resolves10.1109/TIP.2019.2950508
Distilling Channels for Efficient Deep Tracking
resolves10.1109/TCYB.2017.2776977
Feature Distilled Tracking
resolves10.1007/s11042-020-09267-w
Real-time tracking based on deep feature fusion
resolves10.1016/j.asoc.2022.108485
SCSTCF: Spatial-Channel Selection and Temporal Regularized Correlation Filters for visual tracking
resolves10.1016/j.asoc.2015.06.048
CNNTracker: Online discriminative object tracking via deep convolutional neural network
resolves10.1007/s10462-020-09816-7
A comprehensive survey on model compression and acceleration
resolves10.1109/JPROC.2020.2976475
Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey
resolves10.1080/03081087.2016.1267104
Literature survey on low rank approximation of matrices
resolves10.1109/TPAMI.2018.2858826
Focal Loss for Dense Object Detection
resolves10.1109/TIP.2019.2959256
Local Semantic Siamese Networks for Fast Tracking
resolves10.1145/3065386
ImageNet classification with deep convolutional neural networks
resolves10.1109/TPAMI.2014.2388226
Object Tracking Benchmark
resolves10.1109/TIP.2015.2482905
Encoding Color Information for Visual Tracking: Algorithms and Benchmark
resolves10.1109/TPAMI.2019.2957464
GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild
resolves10.1007/s11263-015-0816-y
ImageNet Large Scale Visual Recognition Challenge
The 52 references without a DOI — listed, not checked
no DOI — not checkedref1
no DOI — not checkedDesigning Energy-Efficient Convolutional Neural Networks Using Energy-Aware Pruning
no DOI — not checkedref4
no DOI — not checkedref6
no DOI — not checkedA Twofold Siamese Network for Real-Time Object Tracking
no DOI — not checkedFully-Convolutional Siamese Networks for Object Tracking
no DOI — not checkedref9
no DOI — not checkedLearning Spatially Regularized Correlation Filters for Visual Tracking
no DOI — not checkedCNN Features Off-the-Shelf: An Astounding Baseline for Recognition
no DOI — not checkedHierarchical Convolutional Features for Visual Tracking
no DOI — not checkedCREST: Convolutional Residual Learning for Visual Tracking
no DOI — not checkedECO: Efficient Convolution Operators for Tracking
no DOI — not checkedSiamese Instance Search for Tracking
no DOI — not checkedHigh Performance Visual Tracking with Siamese Region Proposal Network
no DOI — not checkedFast Online Object Tracking and Segmentation: A Unifying Approach
no DOI — not checkedDeeper and Wider Siamese Networks for Real-Time Visual Tracking
no DOI — not checkedSiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks
no DOI — not checkedDeep Residual Learning for Image Recognition
no DOI — not checkedLearning both weights and connections for efficient neural networks
no DOI — not checkedData-free parameter pruning for Deep Neural Networks
no DOI — not checkedPruning Filters for Efficient ConvNets
no DOI — not checkedWeight discretization paradigm for optical neural networks
no DOI — not checkedBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
no DOI — not checkedFixed point quantization of deep convolutional networks
no DOI — not checkedref38
no DOI — not checkedDeterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study
no DOI — not checkedFitNets: Hints for Thin Deep Nets
no DOI — not checkedA Comprehensive Overhaul of Feature Distillation
no DOI — not checkedTask-Oriented Feature Distillation
no DOI — not checkedref43
no DOI — not checkedref44
no DOI — not checkedLearning Background-Aware Correlation Filters for Visual Tracking
no DOI — not checkedUnderstanding the difficulty of training deep feedforward neural networks
no DOI — not checkedDelving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
no DOI — not checkedDistractor-Aware Siamese Networks for Visual Object Tracking
no DOI — not checkedAuto-Encoding Variational Bayes
no DOI — not checkedVisual object tracking for unmanned aerial vehicles: a benchmark and new motion models
no DOI — not checkedLaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking
no DOI — not checkedref56
no DOI — not checkedref57
no DOI — not checkedTrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild
no DOI — not checkedA Large High-Precision Human-Annotated Data Set for Object Detection in Video
no DOI — not checkedLearning Dynamic Siamese Network for Visual Object Tracking
no DOI — not checkedStaple: Complementary Learners for Real-Time Tracking
no DOI — not checkedDiscriminative Correlation Filter with Channel and Spatial Reliability
no DOI — not checkedAdaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking
no DOI — not checkedLearning Spatial-Temporal Regularized Correlation Filters for Visual Tracking
no DOI — not checkedref68
no DOI — not checkedet Visual Tracking via Adaptive Spatially-Regularized Correlation Filters
no DOI — not checkedLearning Multi-domain Convolutional Neural Networks for Visual Tracking
no DOI — not checkedParallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking
no DOI — not checkedVITAL: VIsual Tracking via Adversarial Learning
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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