Robust classification
95 papers with code • 2 benchmarks • 6 datasets
Benchmarks
These leaderboards are used to track progress in Robust classification
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Libraries
Use these libraries to find Robust classification models and implementations
CIFAR-10
MNIST-C
ModelNet40-C
DeepWeeds
N-ImageNet
WHYSHIFT
Most implemented papers
A Fast and Robust TSVM for Pattern Classification
In this paper, we propose a Fast and Robust TSVM~(FR-TSVM) to deal with the above issues.
A generalised framework for detailed classification of swimming paths inside the Morris Water Maze
The Morris Water Maze is commonly used in behavioural neuroscience for the study of spatial learning with rodents.
An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier
We present an end-to-end system combating this variability using a large-area, high-density sensor array and a robust classification algorithm.
HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classification
Compared to previous approaches, we use local memory units to efficiently leverage past temporal information and build a robust event-based representation.
Detecting Multi-Oriented Text with Corner-based Region Proposals
Previous approaches for scene text detection usually rely on manually defined sliding windows.
Weakly Supervised Coupled Networks for Visual Sentiment Analysis
The second branch utilizes both the holistic and localized information by coupling the sentiment map with deep features for robust classification.
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
This work contributes the first large, public, multiclass image dataset of weed species from the Australian rangelands; allowing for the development of robust classification methods to make robotic weed control viable.
Improving Landmark Recognition using Saliency detection and Feature classification
AKASH2907/indian_landmark_recognition
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Image Landmark Recognition has been one of the most sought-after classification challenges in the field of vision and perception.
End-to-End Learning of Representations for Asynchronous Event-Based Data
uzh-rpg/rpg_event_representation_learning
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ICCV 2019
Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events".
GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification
The vulnerabilities of deep neural networks against adversarial examples have become a significant concern for deploying these models in sensitive domains.
