{"url":"/method/vgg-16","slug":"vgg-16","name":"VGG-16","full_name":"VGG-16","full_name_withheld":false,"description_markdown":null,"description_state":"absent","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"http://arxiv.org/abs/1409.1556v6","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Convolutional Neural Networks","url":"/methods/category/convolutional-neural-networks","pwc_aliases":[]}],"n_papers_tagged":46,"archive_num_papers":null,"papers_newest_first":[{"paper":null,"title":"A Unified Anti-Jamming Design in Complex Environments Based on Cross-Modal Fusion and Intelligent Decision-Making","date":"2025-06-09","arxiv_id":"2506.07532","n_code_links":0,"syntology":null},{"paper":null,"title":"Remote Sensing Image Classification with Decoupled Knowledge Distillation","date":"2025-05-25","arxiv_id":"2505.19111","n_code_links":0,"syntology":null},{"paper":null,"title":"Automatic Complementary Separation Pruning Toward Lightweight CNNs","date":"2025-05-19","arxiv_id":"2505.13225","n_code_links":0,"syntology":null},{"paper":null,"title":"Road Segmentation for ADAS/AD Applications","date":"2025-05-18","arxiv_id":"2505.12206","n_code_links":0,"syntology":null},{"paper":null,"title":"Application of Sensitivity Analysis Methods for Studying Neural Network Models","date":"2025-04-21","arxiv_id":"2504.15100","n_code_links":0,"syntology":null},{"paper":null,"title":"Novel Pooling-based VGG-Lite for Pneumonia and Covid-19 Detection from Imbalanced Chest X-Ray Datasets","date":"2025-04-10","arxiv_id":"2504.07468","n_code_links":0,"syntology":null},{"paper":null,"title":"Recursive Self-Similarity in Deep Weight Spaces of Neural Architectures: A Fractal and Coarse Geometry Perspective","date":"2025-03-18","arxiv_id":"2503.14298","n_code_links":0,"syntology":null},{"paper":null,"title":"Adaptive Moment Estimation Optimization Algorithm Using Projection Gradient for Deep Learning","date":"2025-03-13","arxiv_id":"2503.10005","n_code_links":0,"syntology":null},{"paper":null,"title":"JPEG Compliant Compression for Both Human and Machine, A Report","date":"2025-03-13","arxiv_id":"2503.10912","n_code_links":0,"syntology":null},{"paper":null,"title":"Pulling Back the Curtain: Unsupervised Adversarial Detection via Contrastive Auxiliary Networks","date":"2025-02-13","arxiv_id":"2502.09110","n_code_links":0,"syntology":null},{"paper":null,"title":"Performance Evaluation of Image Enhancement Techniques on Transfer Learning for Touchless Fingerprint Recognition","date":"2025-02-07","arxiv_id":"2502.04680","n_code_links":0,"syntology":null},{"paper":null,"title":"P-TAME: Explain Any Image Classifier with Trained Perturbations","date":"2025-01-29","arxiv_id":"2501.17813","n_code_links":0,"syntology":null},{"paper":null,"title":"A Systematic Literature Review on Deep Learning-based Depth Estimation in Computer Vision","date":"2025-01-09","arxiv_id":"2501.05147","n_code_links":0,"syntology":null},{"paper":null,"title":"Optical Character Recognition using Convolutional Neural Networks for Ashokan Brahmi Inscriptions","date":"2024-12-29","arxiv_id":"2501.01981","n_code_links":0,"syntology":null},{"paper":null,"title":"Comparative Analysis of Resource-Efficient CNN Architectures for Brain Tumor Classification","date":"2024-11-23","arxiv_id":"2411.15596","n_code_links":0,"syntology":null},{"paper":null,"title":"Comprehensive and Comparative Analysis between Transfer Learning and Custom Built VGG and CNN-SVM Models for Wildfire Detection","date":"2024-11-12","arxiv_id":"2411.08171","n_code_links":0,"syntology":null},{"paper":null,"title":"A Hybrid Approach for COVID-19 Detection: Combining Wasserstein GAN with Transfer Learning","date":"2024-11-10","arxiv_id":"2411.06397","n_code_links":0,"syntology":null},{"paper":"/paper/an-edge-computing-based-solution-for-real","title":"An Edge Computing-Based Solution for Real-Time Leaf Disease Classification using Thermal Imaging","date":"2024-11-06","arxiv_id":"2411.03835","n_code_links":1,"syntology":null},{"paper":null,"title":"Yoga Pose Classification Using Transfer Learning","date":"2024-10-29","arxiv_id":"2411.00833","n_code_links":0,"syntology":null},{"paper":null,"title":"New Insight in Cervical Cancer Diagnosis Using Convolution Neural Network Architecture","date":"2024-10-23","arxiv_id":"2410.17735","n_code_links":0,"syntology":null},{"paper":"/paper/explainability-of-deep-neural-networks-for","title":"Explainability of Deep Neural Networks for Brain Tumor Detection","date":"2024-10-10","arxiv_id":"2410.07613","n_code_links":1,"syntology":null},{"paper":null,"title":"Comparison of Two Augmentation Methods in Improving Detection Accuracy of Hemarthrosis","date":"2024-09-08","arxiv_id":"2409.05225","n_code_links":0,"syntology":null},{"paper":"/paper/what-makes-a-face-looks-like-a-hat-decoupling","title":"What Makes a Face Look like a Hat: Decoupling Low-level and High-level Visual Properties with Image Triplets","date":"2024-09-03","arxiv_id":"2409.02241","n_code_links":1,"syntology":null},{"paper":null,"title":"H2PIPE: High throughput CNN Inference on FPGAs with High-Bandwidth Memory","date":"2024-08-17","arxiv_id":"2408.09209","n_code_links":0,"syntology":null},{"paper":null,"title":"InfLocNet: Enhanced Lung Infection Localization and Disease Detection from Chest X-Ray Images Using Lightweight Deep Learning","date":"2024-08-12","arxiv_id":"2408.06459","n_code_links":0,"syntology":null},{"paper":null,"title":"TrIM, Triangular Input Movement Systolic Array for Convolutional Neural Networks: Architecture and Hardware Implementation","date":"2024-08-05","arxiv_id":"2408.10243","n_code_links":0,"syntology":null},{"paper":null,"title":"Discriminating retinal microvascular and neuronal differences related to migraines: Deep Learning based Crossectional Study","date":"2024-07-30","arxiv_id":"2408.07293","n_code_links":0,"syntology":null},{"paper":null,"title":"How Does Overparameterization Affect Features?","date":"2024-07-01","arxiv_id":"2407.00968","n_code_links":0,"syntology":null},{"paper":"/paper/baytta-uncertainty-aware-medical-image","title":"BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averaging","date":"2024-06-25","arxiv_id":"2406.17640","n_code_links":1,"syntology":null},{"paper":"/paper/how-to-learn-more-exploring-kolmogorov-arnold","title":"How to Learn More? Exploring Kolmogorov-Arnold Networks for Hyperspectral Image Classification","date":"2024-06-22","arxiv_id":"2406.15719","n_code_links":1,"syntology":null}],"papers_shown":30,"tasks":[{"task":"/task/image-classification","name":"Image Classification","papers":11},{"task":"/task/transfer-learning","name":"Transfer Learning","papers":11},{"task":"/task/classification-1","name":"Classification","papers":8},{"task":"/task/image-classification","name":"image-classification","papers":8},{"task":"/task/data-augmentation","name":"Data Augmentation","papers":3},{"task":"/task/decision-making","name":"Decision Making","papers":3},{"task":"/task/deep-learning","name":"Deep Learning","papers":3},{"task":"/task/activity-recognition","name":"Activity Recognition","papers":2},{"task":"/task/explainable-artificial-intelligence","name":"Explainable artificial intelligence","papers":2},{"task":"/task/human-activity-recognition","name":"Human Activity Recognition","papers":2},{"task":"/task/image-enhancement","name":"Image Enhancement","papers":2},{"task":"/task/management","name":"Management","papers":2},{"task":"/task/medical-diagnosis","name":"Medical Diagnosis","papers":2},{"task":"/task/medical-image-analysis","name":"Medical Image Analysis","papers":2},{"task":"/task/medical-image-classification","name":"Medical Image Classification","papers":2},{"task":"/task/remote-sensing-image-classification","name":"Remote Sensing Image Classification","papers":2},{"task":"/task/segmentation","name":"Segmentation","papers":2},{"task":"/task/sensitivity","name":"Sensitivity","papers":2},{"task":"/task/time-series-1","name":"Time Series","papers":2},{"task":"/task/time-series-classification","name":"Time Series Classification","papers":2}],"tasks_shown":20,"n_tasks":67,"usage_by_year":[{"year":"2014","papers":1},{"year":"2020","papers":2},{"year":"2021","papers":7},{"year":"2022","papers":1},{"year":"2023","papers":1},{"year":"2024","papers":21},{"year":"2025","papers":13}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/vgg-16"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}