SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6501–6550 of 10420 papers

TitleStatusHype
Buffer Zone based Defense against Adversarial Examples in Image Classification—0
Neighbor Class Consistency on Unsupervised Domain Adaptation—0
Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition—0
The simpler the better: vanilla sgd revisited—0
Adaptive Dataset Sampling by Deep Policy Gradient—0
Reducing Implicit Bias in Latent Domain Learning—0
Improving Random-Sampling Neural Architecture Search by Evolving the Proxy Search SpaceCode0
Auto-view contrastive learning for few-shot image recognition—0
Unsupervised Domain Adaptation via Minimized Joint Error—0
A Unified Framework to Analyze and Design the Nonlocal Blocks for Neural Networks—0
Towards Practical Second Order Optimization for Deep Learning—0
Graph Structural Aggregation for Explainable Learning—0
Toward Understanding Supervised Representation Learning with RKHS and GAN—0
NOSE Augment: Fast and Effective Data Augmentation Without Searching—0
Feedforward Legendre Memory Unit—0
Quantifying Task Complexity Through Generalized Information Measures—0
Nonconvex Continual Learning with Episodic Memory—0
MoCo-Pretraining Improves Representations and Transferability of Chest X-ray Models—0
Maximum Categorical Cross Entropy (MCCE): A noise-robust alternative loss function to mitigate racial bias in Convolutional Neural Networks (CNNs) by reducing overfitting—0
LLBoost: Last Layer Perturbation to Boost Pre-trained Neural Networks—0
Lipschitz-Bounded Equilibrium Networks—0
DIET-SNN: A Low-Latency Spiking Neural Network with Direct Input Encoding & Leakage and Threshold Optimization—0
Near-Optimal Glimpse Sequences for Training Hard Attention Neural Networks—0
TaskSet: A Dataset of Optimization TasksCode0
Learning from multiscale wavelet superpixels using GNN with spatially heterogeneous pooling—0
Demystifying Loss Functions for Classification—0
Bayesian Learning to Optimize: Quantifying the Optimizer Uncertainty—0
Achieving Explainability in a Visual Hard Attention Model through Content Prediction—0
Improving the accuracy of neural networks in analog computing-in-memory systems by a generalized quantization method—0
Recall Loss for Imbalanced Image Classification and Semantic SegmentationCode1
The Bootstrap Framework: Generalization Through the Lens of Online Optimization—0
The Foes of Neural Network’s Data Efficiency Among Unnecessary Input Dimensions—0
Counterfactual Thinking for Long-tailed Information Extraction—0
A Gradient-based Kernel Approach for Efficient Network Architecture Search—0
TwinDNN: A Tale of Two Deep Neural Networks—0
Uncertain Out-of-Domain Generalization—0
Optimal allocation of data across training tasks in meta-learning—0
Context-Agnostic Learning Using Synthetic Data—0
Constructing Multiple High-Quality Deep Neural Networks: A TRUST-TECH Based Approach—0
Conditional Networks—0
Certified robustness against physically-realizable patch attack via randomized cropping—0
Dual-Tree Wavelet Packet CNNs for Image Classification—0
More Side Information, Better Pruning: Shared-Label Classification as a Case Study—0
On the Effectiveness of Deep Ensembles for Small Data Tasks—0
Learning Representation in Colour Conversion—0
ROMUL: Scale Adaptative Population Based Training—0
Sparsifying Networks via Subdifferential Inclusion—0
BAFFLE: TOWARDS RESOLVING FEDERATED LEARNING’S DILEMMA - THWARTING BACKDOOR AND INFERENCE ATTACKS—0
AC-VAE: Learning Semantic Representation with VAE for Adaptive Clustering—0
Uncertainty Calibration Error: A New Metric for Multi-Class Classification—0
Show:102550
← PrevPage 131 of 209Next →
All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified