FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class | Paper Citation Record

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This paper cites Machine learning for predicting properties of porous media from 2d x-ray images.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Machine learning for predicting properties of porous media from 2d x-ray images

Reference 1

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This paper cites Digitization and image-based structure-properties relationship evaluation of a porous gold micro-electrode.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Digitization and image-based structure-properties relationship evaluation of a porous gold micro-electrode

Reference 2

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This paper cites Multitask learning: A knowledge-based source of inductive bias1.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Multitask learning: A knowledge-based source of inductive bias1

Reference 3

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This paper cites Predicting the temperature field of thermal cloaks in homogeneous isotropic multilayer materials based on deep learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Predicting the temperature field of thermal cloaks in homogeneous isotropic multilayer materials based on deep learning

Reference 4

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This paper cites Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks

Reference 5

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This paper cites Just pick a sign: Optimizing deep multitask models with gra- dient sign dropout.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Just pick a sign: Optimizing deep multitask models with gra- dient sign dropout

Reference 6

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This paper cites Multinet++: Multi-stream feature ag- gregation and geometric loss strategy for multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Multinet++: Multi-stream feature ag- gregation and geometric loss strategy for multi-task learning

Reference 7

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This paper cites Multi-task deep learning as multi-objective op- timization.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Multi-task deep learning as multi-objective op- timization

Reference 8

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This paper cites Improving image derived vegetation maps with regression based distribution modeling.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Improving image derived vegetation maps with regression based distribution modeling

Reference 9

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This paper cites Dermatologist-level classification of skin cancer with deep neural networks.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Dermatologist-level classification of skin cancer with deep neural networks

Reference 10

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This paper cites Tood: Task-aligned one-stage object detec- tion.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Tood: Task-aligned one-stage object detec- tion

Reference 11

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This paper cites Miti- gating gradient bias in multi-objective learning: A provably convergent approach.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Miti- gating gradient bias in multi-objective learning: A provably convergent approach

Reference 12

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This paper cites Diagnostic ability of heidelberg retina tomograph 3 classifications: glau- coma probability score versus moorfields regression analy- sis.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Diagnostic ability of heidelberg retina tomograph 3 classifications: glau- coma probability score versus moorfields regression analy- sis

Reference 13

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This paper cites Efficiently identifying task groupings for multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Efficiently identifying task groupings for multi-task learning

Reference 14

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This paper cites Ota: Optimal transport assignment for object detection.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Ota: Optimal transport assignment for object detection

Reference 15

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This paper cites Learn- ing to branch for multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Learn- ing to branch for multi-task learning

Reference 16

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This paper cites A multi-task learning-based optimiza- tion approach for finding diverse sets of microstructures with desired properties.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class A multi-task learning-based optimiza- tion approach for finding diverse sets of microstructures with desired properties

Reference 17

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This paper cites Multi-task learning using uncertainty to weigh losses for scene geome- try and semantics.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Multi-task learning using uncertainty to weigh losses for scene geome- try and semantics

Reference 18

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This paper cites Predicting the effective me- chanical property of heterogeneous materials by image based modeling and deep learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Predicting the effective me- chanical property of heterogeneous materials by image based modeling and deep learning

Reference 19

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This paper cites Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection

Reference 20

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This paper cites Libmtl: A python library for deep multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Libmtl: A python library for deep multi-task learning

Reference 21

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This paper cites Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 22

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This paper cites Dual-balancing for multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Dual-balancing for multi-task learning

Reference 23

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This paper cites Smooth Tchebycheff Scalarization for Multi-Objective Optimization.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Smooth Tchebycheff Scalarization for Multi-Objective Optimization

Reference 24

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This paper cites Conflict-averse gradient descent for multi-task learn- ing.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Conflict-averse gradient descent for multi-task learn- ing

Reference 25

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This paper cites Towards impartial multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Towards impartial multi-task learning

Reference 26

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This paper cites End- to-end multi-task learning with attention.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class End- to-end multi-task learning with attention

Reference 27

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This paper cites Asm micrograph database™.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Asm micrograph database™

Reference 28

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This paper cites Modeling task relationships in multi-task learning with multi-gate mixture-of-experts.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Modeling task relationships in multi-task learning with multi-gate mixture-of-experts

Reference 29

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This paper cites An overview of microstruc- tural and material properties of ultra-high-performance con- crete.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class An overview of microstruc- tural and material properties of ultra-high-performance con- crete

Reference 30

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This paper cites Cross-stitch networks for multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Cross-stitch networks for multi-task learning

Reference 31

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This paper cites Electro- formed iron as new biomaterial for degradable stents: Devel- opment process and structure–properties relationship.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Electro- formed iron as new biomaterial for degradable stents: Devel- opment process and structure–properties relationship

Reference 32

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This paper cites Multi-Task Learning as a Bargaining Game.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Multi-Task Learning as a Bargaining Game

Reference 33

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This paper cites Joint classification and trajectory regression of online handwriting using a multi-task learn- ing approach.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Joint classification and trajectory regression of online handwriting using a multi-task learn- ing approach

Reference 34

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This paper cites Testing multivariate adaptive regression splines (mars) as a method of land cover classification of terra-aster satellite im- ages.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Testing multivariate adaptive regression splines (mars) as a method of land cover classification of terra-aster satellite im- ages

Reference 35

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This paper cites Low-latency task-oriented communications with multi-round, multi-task deep learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Low-latency task-oriented communications with multi-round, multi-task deep learning

Reference 36

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This paper cites Multi-task learning as multi-objective optimization.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Multi-task learning as multi-objective optimization

Reference 37

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This paper cites Independent component alignment for multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Independent component alignment for multi-task learning

Reference 38

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This paper cites Which tasks should be learned together in multi-task learning? In International Conference on Machine Learning, pages 9120–9132.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Which tasks should be learned together in multi-task learning? In International Conference on Machine Learning, pages 9120–9132

Reference 39

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This paper cites Mechanical response of human red blood cells in health and disease: Some structure-property-function rela- tionships.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Mechanical response of human red blood cells in health and disease: Some structure-property-function rela- tionships

Reference 40

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This paper cites Progressive layered extraction (ple): A novel multi-task learning (mtl) model for personalized recommendations.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Progressive layered extraction (ple): A novel multi-task learning (mtl) model for personalized recommendations

Reference 41

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This paper cites A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas

Reference 42

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This paper cites Evo- lutionary neural architecture search for image restoration.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Evo- lutionary neural architecture search for image restoration

Reference 43

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This paper cites Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models

Reference 44

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This paper cites Heterogeneous multitask learning with joint sparsity constraints.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Heterogeneous multitask learning with joint sparsity constraints

Reference 45

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This paper cites Gradient surgery for multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Gradient surgery for multi-task learning

Reference 46

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This paper cites A survey on multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class A survey on multi-task learning

Reference 47

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This paper cites Facial landmark detection by deep multi-task learning.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Facial landmark detection by deep multi-task learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:53.688686Z

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Observation ce7c4e26-0f61-41a4-9353-d4c08f175ff1 · outbound

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FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:14:53.506383Z

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