What are the Receptive, Effective Receptive, and Projective Fields of Neurons in Convolutional Neural Networks?

19 May 2017

Papers citing "What are the Receptive, Effective Receptive, and Projective Fields of Neurons in Convolutional Neural Networks?"

9 / 9 papers shown

Title
Learning to Borrow Features for Improved Detection of Small Objects in Single-Shot Detectors Richard Schmit ObjD 101 0 0 30 Apr 2025
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses Chong Xiang Tong Wu Sihui Dai Jonathan Petit Suman Jana Prateek Mittal 54 3 0 19 Oct 2023
Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture Mehraveh Javan Matthew Toews M. Pedersoli 38 1 0 21 Jun 2023
Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance Mats L. Richter C. Pal 27 3 0 26 Nov 2022
Self-Supervised Learning of Perceptually Optimized Block Motion Estimates for Video Compression Somdyuti Paul A. Norkin A. Bovik 20 4 0 05 Oct 2021
Density-embedding layers: a general framework for adaptive receptive fields Francesco Cicala Luca Bortolussi 16 0 0 23 Jun 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 30 29 0 17 May 2020
Evaluation, Tuning and Interpretation of Neural Networks for Meteorological Applications I. Ebert‐Uphoff Kyle Hilburn 29 30 0 06 May 2020
Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval Konstantin Schall Kai Uwe Barthel Nico Hezel Klaus Jung 21 5 0 20 Sep 2019