image classification

The Origins and Prevalence of Texture Bias in Convolutional Neural Networks NeurIPS 2020 Theory-Inspired Path-Regularized Differential Network Architecture Search NeurIPS 2020 Towards Accurate Post-training Network Quantization via Bit-Split and Stitching ICML 2020 Towards Large Yet Imperceptible Adversarial Image Perturbations With Perceptual Color Distance CVPR 2020 Towards Learning Convolutions from Scratch NeurIPS 2020 Towards Oracle Knowledge Distillation with Neural Architecture Search AAAI 2020 Towards Robust Image Classification Using Sequential Attention Models CVPR 2020 Training Linear Finite-State Machines NeurIPS 2020 Understanding Architectures Learnt by Cell-based Neural Architecture Search ICLR 2020 Unrestricted Adversarial Examples via Semantic Manipulation ICLR 2020 Unsupervised Data Augmentation for Consistency Training NeurIPS 2020 Unsupervised Deep Learning via Affinity Diffusion AAAI 2020 UoR at SemEval-2020 Task 8: Gaussian Mixture Modelling (GMM) Based Sampling Approach for Multi-modal Memotion Analysis SemEval 2020 Urszula Walińska at SemEval-2020 Task 8: Fusion of Text and Image Features Using LSTM and VGG16 for Memotion Analysis SemEval 2020 ViP: Virtual Pooling for Accelerating CNN-based Image Classification and Object Detection WACV 2020 Wavelet Integrated CNNs for Noise-Robust Image Classification CVPR 2020 Web-Supervised Network with Softly Update-Drop Training for Fine-Grained Visual Classification AAAI 2020 Zero-Shot Ingredient Recognition by Multi-Relational Graph Convolutional Network AAAI 2020 ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization EMNLP 2020 A Benchmark for Interpretability Methods in Deep Neural Networks NeurIPS 2019 A Comprehensive Overhaul of Feature Distillation ICCV 2019 Active Generative Adversarial Network for Image Classification AAAI 2019 Adaptative Inference Cost With Convolutional Neural Mixture Models ICCV 2019 Adaptively Connected Neural Networks CVPR 2019 Addressing Failure Prediction by Learning Model Confidence NeurIPS 2019