{"url":"/method/inception-resnet-v2-b","slug":"inception-resnet-v2-b","name":"Inception-ResNet-v2-B","full_name":"Inception-ResNet-v2-B","full_name_withheld":false,"description_markdown":"**Inception-ResNet-v2-B** is an image model block for a 17 x 17 grid used in the [Inception-ResNet-v2](https://paperswithcode.com/method/inception-resnet-v2) architecture. It largely follows the idea of Inception modules - and grouped convolutions - but also includes residual connections.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning","paper":"/paper/inception-v4-inception-resnet-and-the-impact","first_author":"Christian Szegedy","n_authors":4,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/inception-v4-inception-resnet-and-the-impact"},"source":{"url":"http://arxiv.org/abs/1602.07261v2","title":"Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/tensorflow/models/blob/e54fcee236a1258302342bd703ee27cbba0c12e3/research/slim/nets/inception_resnet_v2.py#L58","code_snippet_url_on_a_code_host":true,"categories":[{"area":"General","area_id":"general","collection":"Skip Connection Blocks","url":"/methods/category/skip-connection-blocks","pwc_aliases":[]},{"area":"Computer Vision","area_id":"computer-vision","collection":"Image Model Blocks","url":"/methods/category/image-model-blocks","pwc_aliases":[]}],"n_papers_tagged":18,"archive_num_papers":18,"papers_newest_first":[{"paper":null,"title":"Acute Lymphoblastic Leukemia Diagnosis Employing YOLOv11, YOLOv8, ResNet50, and Inception-ResNet-v2 Deep Learning Models","date":"2025-02-13","arxiv_id":"2502.09804","n_code_links":0,"syntology":null},{"paper":"/paper/breccia-and-basalt-classification-of-thin","title":"Breccia and basalt classification of thin sections of Apollo rocks with deep learning","date":"2024-10-28","arxiv_id":"2410.21024","n_code_links":1,"syntology":null},{"paper":"/paper/depth-estimation-from-monocular-images-with","title":"Enhanced Encoder-Decoder Architecture for Accurate Monocular Depth Estimation","date":"2024-10-15","arxiv_id":"2410.11610","n_code_links":1,"syntology":null},{"paper":null,"title":"Hybrid Inception Architecture with Residual Connection: Fine-tuned Inception-ResNet Deep Learning Model for Lung Inflammation Diagnosis from Chest Radiographs","date":"2023-10-04","arxiv_id":"2310.02591","n_code_links":0,"syntology":null},{"paper":null,"title":"A Transfer Learning Based Approach for Classification of COVID-19 and Pneumonia in CT Scan Imaging","date":"2022-10-17","arxiv_id":"2210.09403","n_code_links":0,"syntology":null},{"paper":"/paper/classification-of-breast-tumours-based-on","title":"Classification of Breast Tumours Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods","date":"2022-09-03","arxiv_id":"2209.01380","n_code_links":1,"syntology":null},{"paper":"/paper/danish-fungi-2020-not-just-another-image","title":"Danish Fungi 2020 -- Not Just Another Image Recognition Dataset","date":"2021-03-18","arxiv_id":"2103.10107","n_code_links":1,"syntology":null},{"paper":null,"title":"Attention-Driven Body Pose Encoding for Human Activity Recognition","date":"2020-09-29","arxiv_id":"2009.14326","n_code_links":0,"syntology":null},{"paper":"/paper/an-evaluation-of-dnn-architectures-for-page","title":"An Evaluation of DNN Architectures for Page Segmentation of Historical Newspapers","date":"2020-04-15","arxiv_id":"2004.07317","n_code_links":1,"syntology":null},{"paper":"/paper/skip-connections-matter-on-the","title":"Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets","date":"2020-02-14","arxiv_id":"2002.05990","n_code_links":4,"syntology":{"ran":3,"of":9,"unverified":6,"pointer_only":0}},{"paper":"/paper/2d-and-3d-segmentation-of-uncertain-local","title":"2D and 3D Segmentation of uncertain local collagen fiber orientations in SHG microscopy","date":"2019-07-30","arxiv_id":"1907.12868","n_code_links":1,"syntology":null},{"paper":null,"title":"Multi-Task Self-Supervised Object Detection via Recycling of Bounding Box Annotations","date":"2019-06-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"title":"End-to-End Video Captioning","date":"2019-04-04","arxiv_id":"1904.02628","n_code_links":0,"syntology":null},{"paper":null,"title":"Identifying disease-free chest X-ray images with deep transfer learning","date":"2019-04-02","arxiv_id":"1904.01654","n_code_links":0,"syntology":null},{"paper":null,"title":"Deep neural network ensemble by data augmentation and bagging for skin lesion classification","date":"2018-07-15","arxiv_id":"1807.05496","n_code_links":0,"syntology":null},{"paper":"/paper/deep-koalarization-image-colorization-using","title":"Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2","date":"2017-12-09","arxiv_id":"1712.03400","n_code_links":16,"syntology":null},{"paper":"/paper/polynet-a-pursuit-of-structural-diversity-in","title":"PolyNet: A Pursuit of Structural Diversity in Very Deep Networks","date":"2016-11-17","arxiv_id":"1611.05725","n_code_links":3,"syntology":null},{"paper":"/paper/inception-v4-inception-resnet-and-the-impact","title":"Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning","date":"2016-02-23","arxiv_id":"1602.07261","n_code_links":87,"syntology":{"ran":1,"of":1,"unverified":0,"pointer_only":0}}],"papers_shown":18,"tasks":[{"task":"/task/transfer-learning","name":"Transfer Learning","papers":5},{"task":"/task/decoder","name":"Decoder","papers":3},{"task":"/task/classification","name":"General Classification","papers":3},{"task":"/task/image-classification","name":"Image Classification","papers":3},{"task":"/task/classification-1","name":"Classification","papers":2},{"task":"/task/machine-translation","name":"Machine Translation","papers":2},{"task":"/task/3d-reconstruction","name":"3D Reconstruction","papers":1},{"task":"/task/action-recognition-in-videos","name":"Action Recognition","papers":1},{"task":"/task/activity-recognition","name":"Activity Recognition","papers":1},{"task":"/task/all","name":"All","papers":1},{"task":"/task/breast-cancer-detection","name":"Breast Cancer Detection","papers":1},{"task":"/task/caption-generation","name":"Caption Generation","papers":1},{"task":"/task/classifier-calibration","name":"Classifier calibration","papers":1},{"task":"/task/colorization","name":"Colorization","papers":1},{"task":"/task/contrastive-learning","name":"Contrastive Learning","papers":1},{"task":"/task/data-augmentation","name":"Data Augmentation","papers":1},{"task":"/task/depth-estimation","name":"Depth Estimation","papers":1},{"task":"/task/depth-prediction","name":"Depth Prediction","papers":1},{"task":"/task/diversity","name":"Diversity","papers":1},{"task":"/task/fine-grained-image-classification","name":"Fine-Grained Image Classification","papers":1}],"tasks_shown":20,"n_tasks":42,"usage_by_year":[{"year":"2016","papers":2},{"year":"2017","papers":1},{"year":"2018","papers":1},{"year":"2019","papers":4},{"year":"2020","papers":3},{"year":"2021","papers":1},{"year":"2022","papers":2},{"year":"2023","papers":1},{"year":"2024","papers":2},{"year":"2025","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/inception-resnet-v2-b"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}