{"url":"/method/zfnet","slug":"zfnet","name":"ZFNet","full_name":"ZFNet","full_name_withheld":false,"description_markdown":"**ZFNet** is a classic convolutional neural network. The design was motivated by visualizing intermediate feature layers and the operation of the classifier. Compared to [AlexNet](https://paperswithcode.com/method/alexnet), the filter sizes are reduced and the stride of the convolutions are reduced.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Visualizing and Understanding Convolutional Networks","paper":"/paper/visualizing-and-understanding-convolutional","first_author":"Matthew D. Zeiler","n_authors":2,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/visualizing-and-understanding-convolutional"},"source":{"url":"http://arxiv.org/abs/1311.2901v3","title":"Visualizing and Understanding Convolutional Networks","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/osmr/imgclsmob/blob/bf135f4d635cdc94d89ed5d8bce1f2761fb8593d/pytorch/pytorchcv/models/zfnet.py#L12","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Convolutional Neural Networks","url":"/methods/category/convolutional-neural-networks","pwc_aliases":[]}],"n_papers_tagged":6,"archive_num_papers":6,"papers_newest_first":[{"paper":null,"title":"Compressing neural network by tensor network with exponentially fewer variational parameters","date":"2023-05-10","arxiv_id":"2305.06058","n_code_links":0,"syntology":null},{"paper":null,"title":"A Data Augmented Approach to Transfer Learning for Covid-19 Detection","date":"2021-08-05","arxiv_id":"2108.02870","n_code_links":0,"syntology":null},{"paper":null,"title":"Active deep learning method for the discovery of objects of interest in large spectroscopic surveys","date":"2020-09-07","arxiv_id":"2009.03219","n_code_links":0,"syntology":null},{"paper":null,"title":"Transitioning between Convolutional and Fully Connected Layers in Neural Networks","date":"2017-07-18","arxiv_id":"1707.05743","n_code_links":0,"syntology":null},{"paper":"/paper/spatial-pyramid-pooling-in-deep-convolutional","title":"Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition","date":"2014-06-18","arxiv_id":"1406.4729","n_code_links":14,"syntology":{"ran":0,"of":1,"unverified":1,"pointer_only":0}},{"paper":"/paper/visualizing-and-understanding-convolutional","title":"Visualizing and Understanding Convolutional Networks","date":"2013-11-12","arxiv_id":"1311.2901","n_code_links":18,"syntology":{"ran":2,"of":4,"unverified":2,"pointer_only":3}}],"papers_shown":6,"tasks":[{"task":"/task/classification","name":"General Classification","papers":3},{"task":"/task/image-classification","name":"Image Classification","papers":2},{"task":"/task/active-learning","name":"Active Learning","papers":1},{"task":"/task/covid-19-detection","name":"COVID-19 Diagnosis","papers":1},{"task":"/task/deep-learning","name":"Deep Learning","papers":1},{"task":"/task/object-detection","name":"Object Detection","papers":1},{"task":"/task/object-recognition","name":"Object Recognition","papers":1},{"task":"/task/sensitivity","name":"Sensitivity","papers":1},{"task":"/task/tensor-networks","name":"Tensor Networks","papers":1},{"task":"/task/transfer-learning","name":"Transfer Learning","papers":1},{"task":"/task/video-quality-assessment","name":"Video Quality Assessment","papers":1},{"task":"/task/image-classification","name":"image-classification","papers":1},{"task":"/task/object-detection-1","name":"object-detection","papers":1}],"tasks_shown":13,"n_tasks":13,"usage_by_year":[{"year":"2013","papers":1},{"year":"2014","papers":1},{"year":"2017","papers":1},{"year":"2020","papers":1},{"year":"2021","papers":1},{"year":"2023","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/zfnet"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}