{"id":20442305,"url":"https://github.com/codename-detective/neural-image-classification","last_synced_at":"2025-03-05T07:45:52.467Z","repository":{"id":187775824,"uuid":"677551396","full_name":"CodeName-Detective/Neural-Image-Classification","owner":"CodeName-Detective","description":"Neural Image Classification repository, where cutting-edge deep learning models have been crafted and fine-tuned for diverse image classification tasks. Leveraging state-of-the-art architectures and innovative techniques, this repository stands as a testament to high-performance image recognition.","archived":false,"fork":false,"pushed_at":"2023-08-11T22:45:18.000Z","size":1315,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-15T20:37:30.977Z","etag":null,"topics":["alexnet","computer-vision","deep-learning","image-classification","vgg16"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CodeName-Detective.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}},"created_at":"2023-08-11T21:58:58.000Z","updated_at":"2024-05-21T17:53:06.000Z","dependencies_parsed_at":"2023-08-12T05:08:22.817Z","dependency_job_id":null,"html_url":"https://github.com/CodeName-Detective/Neural-Image-Classification","commit_stats":null,"previous_names":["codename-detective/neural-image-classification"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeName-Detective%2FNeural-Image-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeName-Detective%2FNeural-Image-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeName-Detective%2FNeural-Image-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeName-Detective%2FNeural-Image-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CodeName-Detective","download_url":"https://codeload.github.com/CodeName-Detective/Neural-Image-Classification/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241989843,"owners_count":20053803,"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":["alexnet","computer-vision","deep-learning","image-classification","vgg16"],"created_at":"2024-11-15T09:39:06.395Z","updated_at":"2025-03-05T07:45:52.448Z","avatar_url":"https://github.com/CodeName-Detective.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Neural-Image-Classification\n\n* Developed and trained an initial AlexNet model, and then I modified the AlexNet architecture to enable the classification of three\ncategories: Dogs, Food, and Vehicles. This modification resulted in impressive accuracy rates of 90% and 92.6% for the respective\ncategories. Subsequently, I implemented the VGG-13 model, employing Mixed Precision Training techniques. This approach yielded a\nremarkable accuracy of 91.4%\n\n* Executed the implementation and training of a customized AlexNet model for the classification of Google Street View House\nNumbers, resulting in an impressive accuracy of 91.4%.\n\n* Developed and trained a customized AlexNet model for classifying the OCTMNIST dataset, yielding an accuracy of 71%.\n\n* Created and trained a customized AlexNet model to classify a 10-class ImageNet dataset, achieving an accuracy of 68.4%. Then, I\nimplemented the VGG-13 model and employed Mixed Precision Training, which led to a notable accuracy improvement to 71.8%\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodename-detective%2Fneural-image-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcodename-detective%2Fneural-image-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodename-detective%2Fneural-image-classification/lists"}