{"about":{"site":"https://codewithpapers.app","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.","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"},"url":"/paper/an-empirical-survey-of-data-augmentation-for","title":"An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks","arxiv_id":"2007.15951","date":"2020-07-31","proceeding":null,"authors":["Brian Kenji Iwana","Seiichi Uchida"],"abstract":"In recent times, deep artificial neural networks have achieved many successes in pattern recognition. Part of this success can be attributed to the reliance on big data to increase generalization. However, in the field of time series recognition, many datasets are often very small. One method of addressing this problem is through the use of data augmentation. In this paper, we survey data augmentation techniques for time series and their application to time series classification with neural networks. We propose a taxonomy and outline the four families in time series data augmentation, including transformation-based methods, pattern mixing, generative models, and decomposition methods. Furthermore, we empirically evaluate 12 time series data augmentation methods on 128 time series classification datasets with six different types of neural networks. Through the results, we are able to analyze the characteristics, advantages and disadvantages, and recommendations of each data augmentation method. This survey aims to help in the selection of time series data augmentation for neural network applications.","url_abs":"https://arxiv.org/abs/2007.15951v4","url_pdf":"https://arxiv.org/pdf/2007.15951v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"an-empirical-survey-of-data-augmentation-for","repo_url":"https://github.com/uchidalab/time_series_augmentation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"survey","task_name":"Survey"},{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"},{"task_slug":"time-series-classification","task_name":"Time Series Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2007.15951","atlas_url":"https://app.syntology.ai/?focus=2007.15951","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.15951"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/uchidalab/time_series_augmentation","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":19},"by_repo_kind":{"official":{"samples":19,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"0f0f7c721707eed3","entry":"border_selection","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/prototype_selection.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/prototype_selection.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0f0f7c721707eed3"}},{"code_sha256_prefix":"dbf36d6824e2a63d","entry":"center_selection","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/prototype_selection.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/prototype_selection.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"dbf36d6824e2a63d"}},{"code_sha256_prefix":"03a4fd381f7f635d","entry":"class_offset","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/datasets.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/datasets.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"03a4fd381f7f635d"}},{"code_sha256_prefix":"fe95b56755997e58","entry":"cnn_lenet","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/models.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/models.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"fe95b56755997e58"}},{"code_sha256_prefix":"87f38bda64fde768","entry":"compute_CD","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/nemenyi.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/nemenyi.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"87f38bda64fde768"}},{"code_sha256_prefix":"66037d9834a6eeb5","entry":"dtw","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/dtw.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/dtw.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"66037d9834a6eeb5"}},{"code_sha256_prefix":"e381033c0b9d40ec","entry":"get_datasets","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/input_data.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/input_data.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e381033c0b9d40ec"}},{"code_sha256_prefix":"4c6299e6a59d9118","entry":"get_model","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/models.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/models.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"4c6299e6a59d9118"}},{"code_sha256_prefix":"bb052203a1f1e8df","entry":"graph_ranks","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/nemenyi.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/nemenyi.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"bb052203a1f1e8df"}},{"code_sha256_prefix":"7e91f7d6b90183d5","entry":"jitter","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/augmentation.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/augmentation.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7e91f7d6b90183d5"}},{"code_sha256_prefix":"7cf31f6b78c606a2","entry":"load_data_from_file","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/input_data.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/input_data.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7cf31f6b78c606a2"}},{"code_sha256_prefix":"0297da83a1396658","entry":"mlp4","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/models.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/models.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0297da83a1396658"}},{"code_sha256_prefix":"3213e921153b8366","entry":"nb_classes","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/datasets.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/datasets.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"3213e921153b8366"}},{"code_sha256_prefix":"343f559e28587141","entry":"nb_dims","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/datasets.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/datasets.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"343f559e28587141"}},{"code_sha256_prefix":"43dc9c195316089e","entry":"random_selection","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/prototype_selection.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/prototype_selection.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"43dc9c195316089e"}},{"code_sha256_prefix":"0dfcb65b2964f827","entry":"read_data_sets","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/input_data.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/input_data.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0dfcb65b2964f827"}},{"code_sha256_prefix":"ec568a4fd5c0ca0c","entry":"rotation","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/augmentation.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/augmentation.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"ec568a4fd5c0ca0c"}},{"code_sha256_prefix":"570f35b7d04be7f7","entry":"scaling","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/augmentation.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/augmentation.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"570f35b7d04be7f7"}},{"code_sha256_prefix":"4967a8f159950811","entry":"shape_dtw","repo":"uchidalab/time_series_augmentation","repo_kind":"official","path":"utils/dtw.py","file_url":"https://github.com/uchidalab/time_series_augmentation/blob/HEAD/utils/dtw.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"4967a8f159950811"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}