{"id":29284914,"url":"https://github.com/sarvandani/deep_learning_classification_time_serie_data_seismic","last_synced_at":"2026-04-15T19:36:42.401Z","repository":{"id":301745925,"uuid":"1010191379","full_name":"Sarvandani/Deep_learning_classification_Time_serie_data_seismic","owner":"Sarvandani","description":null,"archived":false,"fork":false,"pushed_at":"2025-06-28T15:06:35.000Z","size":0,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-28T15:38:19.847Z","etag":null,"topics":["deep","deep-learning","keras","matplotlib","numpy","sklearn","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Sarvandani.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-28T14:47:54.000Z","updated_at":"2025-06-28T15:08:51.000Z","dependencies_parsed_at":"2025-06-28T15:49:15.279Z","dependency_job_id":null,"html_url":"https://github.com/Sarvandani/Deep_learning_classification_Time_serie_data_seismic","commit_stats":null,"previous_names":["sarvandani/machine_learning_classification_time_serie_data_seismic"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Sarvandani/Deep_learning_classification_Time_serie_data_seismic","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sarvandani%2FDeep_learning_classification_Time_serie_data_seismic","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sarvandani%2FDeep_learning_classification_Time_serie_data_seismic/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sarvandani%2FDeep_learning_classification_Time_serie_data_seismic/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sarvandani%2FDeep_learning_classification_Time_serie_data_seismic/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Sarvandani","download_url":"https://codeload.github.com/Sarvandani/Deep_learning_classification_Time_serie_data_seismic/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sarvandani%2FDeep_learning_classification_Time_serie_data_seismic/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263813814,"owners_count":23515344,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep","deep-learning","keras","matplotlib","numpy","sklearn","tensorflow"],"created_at":"2025-07-05T22:02:09.768Z","updated_at":"2025-10-24T16:41:38.694Z","avatar_url":"https://github.com/Sarvandani.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep_learning_classification_Time_serie_data_seismic\n\n# Seismic Signal Classification Using CNN\n\nThis project demonstrates how to generate synthetic seismic signals (earthquake and noise), train a 1D Convolutional Neural Network (CNN) to classify signal windows, and visualize classification results on a long mixed seismic signal.\n\n---\n\n## **Overview**\n\nSeismic signals often contain noise and earthquake events that must be distinguished for monitoring and analysis. This repository provides a complete pipeline to:\n\n- **Generate synthetic seismic signals** simulating earthquake bursts and noise.\n- **Visualize sample signals** to understand class characteristics.\n- **Train a CNN model** to classify fixed-length windows of seismic data as earthquake or noise.\n- **Apply the trained model** to a long mixed signal and visualize the classification over time.\n\n---\n\n## **Features**\n\n- Synthetic data generation with controlled noise and earthquake bursts.\n- Labeled visualization of example earthquake and noise signals.\n- 1D CNN architecture tailored for time-series classification.\n- Model training with validation and test splits.\n- Window-by-window classification of long seismic signals.\n- Visualization of classification results with color-coded plots (red = earthquake, blue = noise).\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsarvandani%2Fdeep_learning_classification_time_serie_data_seismic","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsarvandani%2Fdeep_learning_classification_time_serie_data_seismic","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsarvandani%2Fdeep_learning_classification_time_serie_data_seismic/lists"}