{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/cell-detection/papers/2","list_of":"/task/cell-detection","task":"Cell Detection","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":2,"rows_per_page":100,"rows":[101,132],"of":132,"counts":{"archive_papers_tagged":132,"with_a_code_link":60,"where_syntology_ran_a_sample":6,"not_listed_spam_title":0,"listed":132,"listed_where_code_ran":6,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":5,"every_run_a_failure_of_syntologys_instrument":1,"listed_with_a_run_with_no_instrument_failure":5,"listed_every_run_a_failure_of_syntologys_instrument":1,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/cell-detection","prev":"/task/cell-detection","next":null,"papers":[{"url":null,"slug":"deep-semi-supervised-metric-learning-with","title":"Deep Semi-supervised Metric Learning with Dual Alignment for Cervical Cancer Cell Detection","date":"2021-04-07","arxiv_id":"2104.03265","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-spatial-analysis-in","title":"Probabilistic Spatial Analysis in Quantitative Microscopy with Uncertainty-Aware Cell Detection using Deep Bayesian Regression of Density Maps","date":"2021-02-23","arxiv_id":"2102.11865","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-cell-and-protein-concentrations-by","title":"Detecting cell and protein concentrations by the use of a thermal based sensor","date":"2021-02-16","arxiv_id":"2102.08335","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-be-exact-cell-detection-for","title":"Learning to be EXACT, Cell Detection for Asthma on Partially Annotated Whole Slide Images","date":"2021-01-13","arxiv_id":"2101.04943","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-network-fast-classifies-biological","title":"Neural network fast-classifies biological images using features selected after their random-forests-importance to power smart microscopy","date":"2020-12-18","arxiv_id":"2012.10331","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiscale-detection-of-cancerous-tissue-in","title":"Multiscale Detection of Cancerous Tissue in High Resolution Slide Scans","date":"2020-10-01","arxiv_id":"2010.00641","repositories_listed":0,"syntology":null},{"url":null,"slug":"hydramix-net-a-deep-multi-task-semi","title":"HydraMix-Net: A Deep Multi-task Semi-supervised Learning Approach for Cell Detection and Classification","date":"2020-08-11","arxiv_id":"2008.04753","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-human-mesenchymal-stromal-cells-to","title":"From Human Mesenchymal Stromal Cells to Osteosarcoma Cells Classification by Deep Learning","date":"2020-08-04","arxiv_id":"2008.01864","repositories_listed":0,"syntology":null},{"url":null,"slug":"macd-r-cnn-an-abnormal-cell-nucleus-detection","title":"MACD R-CNN: An Abnormal Cell Nucleus Detection Method","date":"2020-07-28","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"negative-pseudo-labeling-using-class","title":"Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology","date":"2020-07-16","arxiv_id":"2007.08044","repositories_listed":0,"syntology":null},{"url":null,"slug":"detcid-detection-of-elongated-touching-cells","title":"DETCID: Detection of Elongated Touching Cells with Inhomogeneous Illumination using a Deep Adversarial Network","date":"2020-07-13","arxiv_id":"2007.06716","repositories_listed":0,"syntology":null},{"url":null,"slug":"ganglionnet-objectively-assess-the-density","title":"GanglionNet: Objectively Assess the Density and Distribution of Ganglion Cells With NABLA-N Network","date":"2020-07-05","arxiv_id":"2007.02367","repositories_listed":0,"syntology":null},{"url":"/paper/global-table-extractor-gte-a-framework-for","slug":"global-table-extractor-gte-a-framework-for","title":"Global Table Extractor (GTE): A Framework for Joint Table Identification and Cell Structure Recognition Using Visual Context","date":"2020-05-01","arxiv_id":"2005.00589","repositories_listed":0,"syntology":null},{"url":null,"slug":"decoupled-gradient-harmonized-detector-for","title":"Decoupled Gradient Harmonized Detector for Partial Annotation: Application to Signet Ring Cell Detection","date":"2020-04-09","arxiv_id":"2004.04455","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepsperm-a-robust-and-real-time-bull-sperm","title":"DeepSperm: A robust and real-time bull sperm-cell detection in densely populated semen videos","date":"2020-03-03","arxiv_id":"2003.01395","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-multi-task-learning-for","title":"Weakly Supervised Multi-Task Learning for Cell Detection and Segmentation","date":"2019-10-27","arxiv_id":"1910.12326","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-label-detection-and-classification-of","title":"Multi-label Detection and Classification of Red Blood Cells in Microscopic Images","date":"2019-10-07","arxiv_id":"1910.02672","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-machine-learning-framework-for-sleeping","title":"A Machine Learning framework for Sleeping Cell Detection in a Smart-city IoT Telecommunications Infrastructure","date":"2019-10-02","arxiv_id":"1910.01092","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-deep-learning-models-for-multi-cell","title":"Comparing Deep Learning Models for Multi-cell Classification in Liquid-based Cervical Cytology Images","date":"2019-10-02","arxiv_id":"1910.00722","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-blood-cell-detection-and-counting","title":"Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices","date":"2019-09-11","arxiv_id":"1909.05393","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepdistance-a-multi-task-deep-regression","title":"DeepDistance: A Multi-task Deep Regression Model for Cell Detection in Inverted Microscopy Images","date":"2019-08-29","arxiv_id":"1908.11211","repositories_listed":0,"syntology":null},{"url":null,"slug":"concorde-net-cell-count-regularized","title":"ConCORDe-Net: Cell Count Regularized Convolutional Neural Network for Cell Detection in Multiplex Immunohistochemistry Images","date":"2019-08-01","arxiv_id":"1908.00907","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhanced-center-coding-for-cell-detection","title":"Enhanced Center Coding for Cell Detection with Convolutional Neural Networks","date":"2019-04-18","arxiv_id":"1904.08864","repositories_listed":0,"syntology":null},{"url":null,"slug":"cell-detection-on-image-based-immunoassays","title":"Cell detection on image-based immunoassays","date":"2018-10-23","arxiv_id":"1810.09707","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-convolutional-neural-networks-and","title":"Training Convolutional Neural Networks and Compressed Sensing End-to-End for Microscopy Cell Detection","date":"2018-10-07","arxiv_id":"1810.03075","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-processing-and-solar-cell-detection","title":"Automatic Processing and Solar Cell Detection in Photovoltaic Electroluminescence Images","date":"2018-07-26","arxiv_id":"1807.10820","repositories_listed":0,"syntology":null},{"url":null,"slug":"deconvolving-convolution-neural-network-for","title":"Deconvolving convolution neural network for cell detection","date":"2018-06-18","arxiv_id":"1806.06970","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-25d-cascaded-convolutional-neural-network","title":"A 2.5D Cascaded Convolutional Neural Network with Temporal Information for Automatic Mitotic Cell Detection in 4D Microscopic Images","date":"2018-06-04","arxiv_id":"1806.01018","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-cell-detection-and-classification-using","title":"Multi-Cell Detection and Classification Using a Generative Convolutional Model","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-column-generation-for-cell","title":"Efficient Column Generation for Cell Detection and Segmentation","date":"2017-09-21","arxiv_id":"1709.07337","repositories_listed":0,"syntology":null},{"url":null,"slug":"isotachophoresis-applied-to-chemical","title":"Isotachophoresis applied to chemical reactions","date":"2017-08-28","arxiv_id":"1708.08298","repositories_listed":0,"syntology":null},{"url":null,"slug":"appearance-invariance-in-convolutional","title":"Appearance invariance in convolutional networks with neighborhood similarity","date":"2017-07-03","arxiv_id":"1707.00755","repositories_listed":0,"syntology":null}],"record_sha256":"fbed566906a2876f53b594f982667b959f9f8039d92e5d203540d920ec94df35","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}