Vision Transformers for Weakly-Supervised Microorganism Enumeration | Paper Citation Record

Observation ffeb3d30-71b2-46e8-9a90-94e2598d0a95 · outbound

This paper cites High-throughput imaging of bacterial colonies grown on filter plates with application to serum bactericidal assays,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration High-throughput imaging of bacterial colonies grown on filter plates with application to serum bactericidal assays,

Reference 1

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Observation d32584e4-cddb-42c9-92bb-80ac45655d8c · outbound

This paper cites Applicability of solid-phase cytometry and epifluorescence microscopy for rapid assessment of the microbio- logical quality of dialysis water,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Applicability of solid-phase cytometry and epifluorescence microscopy for rapid assessment of the microbio- logical quality of dialysis water,

Reference 2

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Observation 417e8040-e777-40f3-b181-e824a4a9f892 · outbound

This paper cites Use of fluorochromes for direct enumeration of total bacteria in environmental samples: past and present,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Use of fluorochromes for direct enumeration of total bacteria in environmental samples: past and present,

Reference 3

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This paper cites an unresolved cited work.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Unresolved cited work

Reference 4

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Observation c3f40064-8f11-4118-8c53-df22da52a0af · outbound

This paper cites Horwitz, Official methods of analysis of the Association of Official Analytical Chemists.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Horwitz, Official methods of analysis of the Association of Official Analytical Chemists

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:40.424600Z

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Observation 4c0d0efe-592f-4928-9d1d-eb483439a023 · outbound

This paper cites Absher, CHAPTER 1 - Hemocytometer Counting , p.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Absher, CHAPTER 1 - Hemocytometer Counting , p

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:40.271665Z

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Observation b8a4d144-dccb-42b9-a120-fa26c7e8ca6c · outbound

This paper cites an unresolved cited work.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Unresolved cited work

Reference 7

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Observation 6ca06ef2-86cd-4bbe-aa6a-f018c22d6f1c · outbound

This paper cites A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:39.874748Z

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Observation 0b3706bb-d9a6-497c-975c-581421de8a30 · outbound

This paper cites DeepBacs: Bacterial image analysis using open-source deep learning approaches,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration DeepBacs: Bacterial image analysis using open-source deep learning approaches,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:39.694823Z

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Observation f9c8e5e8-48ec-4d81-a8cf-58afb409ab8f · outbound

This paper cites Democratising deep learning for microscopy with ZeroCostDL4Mic,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Democratising deep learning for microscopy with ZeroCostDL4Mic,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:39.488213Z

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Observation ded1223b-13c8-4187-8d18-06784867de5f · outbound

This paper cites Automatic bacillus anthracis bacteria detection and segmentation in microscopic images using unet++,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Automatic bacillus anthracis bacteria detection and segmentation in microscopic images using unet++,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:39.314740Z

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Observation 213d41ff-8a14-4c73-bc84-def5ac27b2fc · outbound

This paper cites Deeply-Supervised Density Regression for Automatic Cell Counting in Microscopy Images.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Deeply-Supervised Density Regression for Automatic Cell Counting in Microscopy Images

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:43:35.236100Z

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Observation d70c0edb-7950-4874-b3d7-77488e3d54c6 · outbound

This paper cites Evaluation of two methods for monitoring surface cleanliness-atp bioluminescence and traditional hygiene swabbing.,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Evaluation of two methods for monitoring surface cleanliness-atp bioluminescence and traditional hygiene swabbing.,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:39.281533Z

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Observation 5a3d956d-f4d7-4c33-b22e-253c7e33fd40 · outbound

This paper cites Cell Counting by Regression Using Convolutional Neural Network,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Cell Counting by Regression Using Convolutional Neural Network,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:39.214760Z

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Observation 35d2f080-a4dd-455f-b6a3-f0032f2a72be · outbound

This paper cites Classification Beats Regression: Counting of Cells from Greyscale Microscopic Images based on Annotation-free Training Samples.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Classification Beats Regression: Counting of Cells from Greyscale Microscopic Images based on Annotation-free Training Samples

Reference 15

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Observation 5025bde4-225d-4fc2-a831-a6895d6a6b27 · outbound

This paper cites CounTR: Transformer-based Generalised Visual Counting.

Vision Transformers for Weakly-Supervised Microorganism Enumeration CounTR: Transformer-based Generalised Visual Counting

Reference 16

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Observation 6eb62e51-91ec-4b82-9bf7-9434bbc5dd60 · outbound

This paper cites TransCrowd: weakly-supervised crowd counting with transformers.

Vision Transformers for Weakly-Supervised Microorganism Enumeration TransCrowd: weakly-supervised crowd counting with transformers

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:43:34.665096Z

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Observation 109f180d-ba1c-4651-ac4e-3b3ac869ef24 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T23:43:30.984747Z

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Observation 1c6ad987-8825-488f-a78a-090500108a60 · outbound

This paper cites Automating cell counting in fluorescent microscopy through deep learning with c-resunet,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Automating cell counting in fluorescent microscopy through deep learning with c-resunet,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:39.055822Z

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Observation 8581ad4c-3af8-4d89-9d6d-2203fe3da111 · outbound

This paper cites Learning to count objects in images,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Learning to count objects in images,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:38.892713Z

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Observation afdc4ec3-31bd-4c74-bb8b-4ddcc4e664f4 · outbound

This paper cites Microscope images of human cancer cell lines (u2os and hl-60),.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Microscope images of human cancer cell lines (u2os and hl-60),

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:38.758003Z

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Observation 1f8e278b-929b-481c-9dad-24eeda5493d1 · outbound

This paper cites Transformers in Vision: A Survey.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Transformers in Vision: A Survey

Reference 22

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Observation 4c17fe66-95c5-4875-8baf-e832d6b905e0 · outbound

This paper cites Monitoring micorbial morphogenetic changes in a fermentation process by a self- tuning vision system (stvs),.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Monitoring micorbial morphogenetic changes in a fermentation process by a self- tuning vision system (stvs),

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:38.650979Z

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Observation 08d08e52-09d7-4316-9a04-f75efe2f80e8 · outbound

This paper cites U-net: deep learning for cell counting, detection, and morphometry,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration U-net: deep learning for cell counting, detection, and morphometry,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:38.404892Z

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Observation ad40d925-e62b-41b0-94b9-47f3930f12a0 · outbound

This paper cites Automating cell counting in fluorescent microscopy through deep learning with c-resunet,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Automating cell counting in fluorescent microscopy through deep learning with c-resunet,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:38.214829Z

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Observation 6a726f10-b39a-4c27-98dd-49fc6a112908 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Vision Transformers for Weakly-Supervised Microorganism Enumeration U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T23:43:31.304747Z

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Observation cfcac717-5470-4166-9ff5-39c294c259b0 · outbound

This paper cites Microscopy cell counting and detection with fully convolutional regression networks,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Microscopy cell counting and detection with fully convolutional regression networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:38.036111Z

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Observation 353dcd95-ec8e-451f-9da2-da8675f17854 · outbound

This paper cites Automatic microscopic cell counting by use of deeply-supervised density regression model.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Automatic microscopic cell counting by use of deeply-supervised density regression model

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:43:34.364895Z

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Observation 5f662640-5b3c-4677-9b84-cfd1c73b3c9b · outbound

This paper cites Efficient and robust cell detection: A structured regression approach,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Efficient and robust cell detection: A structured regression approach,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:37.934748Z

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Observation e26a30b8-144f-4f93-9e5f-4f9e01b556e7 · outbound

This paper cites Weakly Supervised Learning for cell recognition in immunohistochemical cytoplasm staining images.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Weakly Supervised Learning for cell recognition in immunohistochemical cytoplasm staining images

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:43:34.214743Z

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Observation 08d3b79c-0e8e-46a0-ac0f-e4b6f850ab1d · outbound

This paper cites Deep convolutional neural networks for human embryonic cell counting,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Deep convolutional neural networks for human embryonic cell counting,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:37.676245Z

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Observation 5a86c718-257d-44a2-ad1c-ba141af1caa0 · outbound

This paper cites CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model.

Vision Transformers for Weakly-Supervised Microorganism Enumeration CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model

Reference 32

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Observation fb2ecfc9-09a7-435b-a8e6-337151f96a45 · outbound

This paper cites Deep learning and transfer learning for automatic cell counting in microscope images of human cancer cell lines,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Deep learning and transfer learning for automatic cell counting in microscope images of human cancer cell lines,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:37.614751Z

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Observation decf9d21-5199-4d2f-9c43-8211098ce790 · outbound

This paper cites Context-aware crowd counting,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Context-aware crowd counting,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:37.477625Z

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Observation 304ef06a-b137-4fd7-832c-ce7e47bf01a7 · outbound

This paper cites CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability.

Vision Transformers for Weakly-Supervised Microorganism Enumeration CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:43:33.908670Z

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Observation 75108d45-7007-407c-9ee3-a201fae6cb99 · outbound

This paper cites Dtcc: Multi- level dilated convolution with transformer for weakly-supervised crowd counting,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Dtcc: Multi- level dilated convolution with transformer for weakly-supervised crowd counting,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:37.323080Z

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Observation 14af6c5a-f8e1-45d1-8d65-f8249109fd06 · outbound

This paper cites Transformer-based visual segmentation: A survey,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Transformer-based visual segmentation: A survey,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:37.213149Z

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Observation 2b262dea-47fe-4670-9675-5afe0fa7fef0 · outbound

This paper cites Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Reference 38

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Observation 6b0dd332-9d0a-4537-aaf3-37e1f9d8d055 · outbound

This paper cites Rethinking Global Context in Crowd Counting.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Rethinking Global Context in Crowd Counting

Reference 39

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Observation b74a0971-089b-42e1-b16f-786753fdbea5 · outbound

This paper cites CCTrans: Simplifying and Improving Crowd Counting with Transformer.

Vision Transformers for Weakly-Supervised Microorganism Enumeration CCTrans: Simplifying and Improving Crowd Counting with Transformer

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T23:43:32.204831Z

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Observation 018f1966-e080-46b4-a3f2-bc23bec76f7b · outbound

This paper cites Joint CNN and Transformer Network via weakly supervised Learning for efficient crowd counting.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Joint CNN and Transformer Network via weakly supervised Learning for efficient crowd counting

Reference 41

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Observation bebf9735-9aab-4555-9b49-34dd900ce8b2 · outbound

This paper cites Cctwins: A weakly- supervised transformer-based crowd counting method with adaptive scene consistency attention,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Cctwins: A weakly- supervised transformer-based crowd counting method with adaptive scene consistency attention,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:36.974898Z

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Observation 3a1cf231-edd2-4651-920c-d6206e7bccfe · outbound

This paper cites Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervision.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervision

Reference 43

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Observation 0515e42f-30d3-4f34-910d-e705dc308c64 · outbound

This paper cites Weakly-supervised crowd counting learns from sorting rather than locations,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Weakly-supervised crowd counting learns from sorting rather than locations,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:36.764830Z

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Observation 345c7a05-f8e9-438b-bec9-6f7a030da2f4 · outbound

This paper cites Towards using count-level weak supervision for crowd counting,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Towards using count-level weak supervision for crowd counting,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:36.628577Z

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Observation 8179e3eb-c734-4639-87ce-21dc09a8550b · outbound

This paper cites Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:36.434830Z

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Observation ddd47316-d4f6-4e4a-9c4f-257f15555a8b · outbound

This paper cites Bayesian loss for crowd count estimation with point supervision,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Bayesian loss for crowd count estimation with point supervision,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:36.314115Z

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Observation 0daa8792-5129-42f4-89dc-66f410465e6a · outbound

This paper cites Deepvit: Towards deeper vision transformer,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Deepvit: Towards deeper vision transformer,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:36.164750Z

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Observation fe902a21-6a48-4a68-a786-64e9d04454fa · outbound

This paper cites Crossvit: Cross-attention multi-scale vision transformer for image classification,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Crossvit: Cross-attention multi-scale vision transformer for image classification,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:36.000219Z

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Observation 9418897d-d4ed-4740-be97-e80ef72397f1 · outbound

This paper cites Three things everyone should know about vision transformers,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Three things everyone should know about vision transformers,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:35.824913Z

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Observation eec778e2-bcaa-4620-83e0-abaf81a1aaa1 · outbound

This paper cites Xcit: Cross-covariance image transformers,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Xcit: Cross-covariance image transformers,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:43:35.594831Z

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Observation 4d46444b-c137-468c-afaa-cc23bd126a8f · outbound

This paper cites Deep Residual Learning for Image Recognition.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Deep Residual Learning for Image Recognition

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T23:43:33.004751Z

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Observation eaef5037-3fab-425b-b126-58722a366a33 · outbound

This paper cites On Layer Normalization in the Transformer Architecture.

Vision Transformers for Weakly-Supervised Microorganism Enumeration On Layer Normalization in the Transformer Architecture

Reference 53

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This paper cites Computational framework for simulating fluorescence microscope images with cell populations,.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Computational framework for simulating fluorescence microscope images with cell populations,

Reference 54

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This paper cites Context-Aware Crowd Counting.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Context-Aware Crowd Counting

Reference 2019

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This paper cites Transformer-Based Visual Segmentation: A Survey.

Vision Transformers for Weakly-Supervised Microorganism Enumeration Transformer-Based Visual Segmentation: A Survey

Reference 2023

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