Paper Citation Record · LEDGER

Needles in Haystacks: On Classifying Tiny Objects in Large Images

As of 22 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:1908.06037.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.06037 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:02:09.745819Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation 968c87a5-bd6f-4035-a374-e80a41324b98 · outbound

This paper cites write newline.

Needles in Haystacks: On Classifying Tiny Objects in Large Images write newline

Reference 1

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Observation 14adfa3d-0089-4055-8d72-7d0f61beb951 · outbound

This paper cites Dynamic capacity networks.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Dynamic capacity networks

Reference 2

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Observation be4e6022-d677-4cc3-ab11-8252257193ba · outbound

This paper cites BACH: Grand Challenge on Breast Cancer Histology Images.

Needles in Haystacks: On Classifying Tiny Objects in Large Images BACH: Grand Challenge on Breast Cancer Histology Images

Reference 3

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This paper cites Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S

Reference 4

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Observation fad7bc4a-31ee-4368-97be-92675f832e13 · outbound

This paper cites Multiple object recognition with visual attention.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Multiple object recognition with visual attention

Reference 5

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Observation cacb811c-e148-44a4-8ee4-e057d0cf46f8 · outbound

This paper cites Benchmarking of image registration methods for differently stained histological slides.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Benchmarking of image registration methods for differently stained histological slides

Reference 6

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Observation a02f6ab8-d719-4f4f-85e5-1eb2e62fdf7e · outbound

This paper cites Approximating CNN s with bag-of-local-features models works surprisingly well on imagenet.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Approximating CNN s with bag-of-local-features models works surprisingly well on imagenet

Reference 7

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Observation 27cf46ec-c124-48ae-ae9f-c0dd426551b0 · outbound

This paper cites Bándi , O.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Bándi , O

Reference 8

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Needles in Haystacks: On Classifying Tiny Objects in Large Images Unresolved cited work

Reference 9

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Observation ad49eaaf-e6b3-4ca2-8839-3d7484fadba9 · outbound

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Needles in Haystacks: On Classifying Tiny Objects in Large Images Unresolved cited work

Reference 10

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Observation 4f487ae1-d876-4709-b055-a71a9c12faa2 · outbound

This paper cites Deep Learning.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Deep Learning

Reference 11

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Observation 6ae1c408-89c5-46e7-914f-020647157d17 · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Co-teaching: Robust training of deep neural networks with extremely noisy labels

Reference 12

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Observation 7751ec0d-6449-4915-82d7-3a712f170f8d · outbound

This paper cites Where's Wally? Walker, 1987.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Where's Wally? Walker, 1987

Reference 13

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Observation 0b2e4801-7e84-44c3-8056-9f29ec96e19f · outbound

This paper cites Deep Residual Learning for Image Recognition.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Deep Residual Learning for Image Recognition

Reference 14

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Observation e17864db-ea7d-4469-9d77-6c503f49e63e · outbound

This paper cites Identity mappings in deep residual networks.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Identity mappings in deep residual networks

Reference 15

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This paper cites Densely connected convolutional networks.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Densely connected convolutional networks

Reference 16

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Observation 47a04be9-4b10-4373-8061-db5cd36e6866 · outbound

This paper cites Attention-based Deep Multiple Instance Learning.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Attention-based Deep Multiple Instance Learning

Reference 17

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Observation 2ecf5752-6f9a-47b9-990d-502b4d03fd9c · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 18

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This paper cites Three Factors Influencing Minima in SGD.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Three Factors Influencing Minima in SGD

Reference 19

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Observation 63ef3882-18b4-4544-b4b0-11c9b07ec236 · outbound

This paper cites MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels.

Needles in Haystacks: On Classifying Tiny Objects in Large Images MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels

Reference 20

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Observation 9e4c5e43-69ce-48ca-81ad-941f33abe130 · outbound

This paper cites Processing Megapixel Images with Deep Attention-Sampling Models.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Processing Megapixel Images with Deep Attention-Sampling Models

Reference 21

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Observation 5fad7679-541f-4db2-be32-4553e8a94335 · outbound

This paper cites Learning multiple layers of features from tiny images.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Learning multiple layers of features from tiny images

Reference 22

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Observation 4b15c51d-c5d1-4aea-bc93-fef4e54437a2 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Imagenet classification with deep convolutional neural networks

Reference 23

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Observation de4b0f1e-6f91-4e76-b6da-65f99daa1735 · outbound

This paper cites The handbook of brain theory and neural networks.

Needles in Haystacks: On Classifying Tiny Objects in Large Images The handbook of brain theory and neural networks

Reference 24

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Observation 28337e38-c45c-4e8e-8ade-b12f7cdf9d79 · outbound

This paper cites Gradient-based learning applied to document recognition.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Gradient-based learning applied to document recognition

Reference 25

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Observation c0169e2a-b424-429d-9f1b-204a2a4341cf · outbound

This paper cites A Robust and Effective Approach Towards Accurate Metastasis Detection and pN-stage Classification in Breast Cancer.

Needles in Haystacks: On Classifying Tiny Objects in Large Images A Robust and Effective Approach Towards Accurate Metastasis Detection and pN-stage Classification in Breast Cancer

Reference 26

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This paper cites Microsoft COCO: Common objects in context.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Microsoft COCO: Common objects in context

Reference 27

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Observation e8b680bb-c143-4b0a-9c5b-a87e15033868 · outbound

This paper cites Exploring the limits of weakly supervised pretraining.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Exploring the limits of weakly supervised pretraining

Reference 28

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Observation be4ece2b-7ec2-4ac5-8e68-32b6ebe3436f · outbound

This paper cites Recurrent models of visual attention.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Recurrent models of visual attention

Reference 29

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This paper cites Abolafia, Jeffrey Pennington, and Jascha Sohl-Dickstein.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Abolafia, Jeffrey Pennington, and Jascha Sohl-Dickstein

Reference 30

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Observation a3e0d570-75ec-41be-bacd-551cfd5bbff2 · outbound

This paper cites Is object localization for free?-weakly-supervised learning with convolutional neural networks.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Is object localization for free?-weakly-supervised learning with convolutional neural networks

Reference 31

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This paper cites R$^2$-CNN: Fast Tiny Object Detection in Large-Scale Remote Sensing Images.

Needles in Haystacks: On Classifying Tiny Objects in Large Images R$^2$-CNN: Fast Tiny Object Detection in Large-Scale Remote Sensing Images

Reference 32

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This paper cites Resta , N.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Resta , N

Reference 33

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Needles in Haystacks: On Classifying Tiny Objects in Large Images Berens, Cas van den Bogaard, Piergiorgio Cerello, Hao Chen, Qi Dou, Maria Evelina Fantacci, Bram Geurts, Robbert van der Gugten, Pheng Ann Heng, Bart Jansen, Michael M.J

Reference 34

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This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 35

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This paper cites The mammographic image analysis society digital mammogram database''exerpta medica.

Needles in Haystacks: On Classifying Tiny Objects in Large Images The mammographic image analysis society digital mammogram database''exerpta medica

Reference 36

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This paper cites 3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects.

Needles in Haystacks: On Classifying Tiny Objects in Large Images 3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects

Reference 37

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This paper cites Revisiting unreasonable effectiveness of data in deep learning era.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Revisiting unreasonable effectiveness of data in deep learning era

Reference 38

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Needles in Haystacks: On Classifying Tiny Objects in Large Images Tieleman and G

Reference 39

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This paper cites Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides

Reference 40

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This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 41

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This paper cites Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks

Reference 42

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This paper cites Dota: A large-scale dataset for object detection in aerial images.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Dota: A large-scale dataset for object detection in aerial images

Reference 43

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This paper cites Understanding deep learning requires rethinking generalization.

Needles in Haystacks: On Classifying Tiny Objects in Large Images Understanding deep learning requires rethinking generalization

Reference 44

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Needles in Haystacks: On Classifying Tiny Objects in Large Images @esa (Ref

Reference 45

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Reference 47

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Pith citing papers

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