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 5351–5400 of 10420 papers

TitleStatusHype
MLP-based architecture with variable length input for automatic speech recognition—0
Hermitry Ratio: Evaluating the validity of perturbation methods for explainable deep learning—0
GUIDED MCMC FOR SPARSE BAYESIAN MODELS TO DETECT RARE EVENTS IN IMAGES SANS LABELED DATA—0
Ontology-Driven Semantic Alignment of Artificial Neurons and Visual Concepts—0
Fundamental Limits of Transfer Learning in Binary Classifications—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Assessing two novel distance-based loss functions for few-shot image classification—0
FLOAT: FAST LEARNABLE ONCE-FOR-ALL ADVERSARIAL TRAINING FOR TUNABLE TRADE-OFF BETWEEN ACCURACY AND ROBUSTNESS—0
Meta-OLE: Meta-learned Orthogonal Low-Rank Embedding—0
Compositional Training for End-to-End Deep AUC Maximization—0
FedBABU: Toward Enhanced Representation for Federated Image Classification—0
Feature Kernel Distillation—0
Two Birds, One Stone: Achieving both Differential Privacy and Certified Robustness for Pre-trained Classifiers via Input Perturbation—0
Noise-Contrastive Variational Information Bottleneck Networks—0
Sphere2Vec: Self-Supervised Location Representation Learning on Spherical Surfaces—0
Less is More: Dimension Reduction Finds On-Manifold Adversarial Examples in Hard-Label Attacks—0
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet TrainingCode1
Tessellated 2D Convolution Networks: A Robust Defence against Adversarial Attacks—0
Measuring the Effectiveness of Self-Supervised Learning using Calibrated Learning Curves—0
Neural Extensions: Training Neural Networks with Set Functions—0
Rank4Class: Examining Multiclass Classification through the Lens of Learning to Rank—0
DM-CT: Consistency Training with Data and Model Perturbation—0
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions—0
Towards Efficient On-Chip Training of Quantum Neural Networks—0
Pseudo Knowledge Distillation: Towards Learning Optimal Instance-specific Label Smoothing Regularization—0
Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods—0
To Smooth or not to Smooth? On Compatibility between Label Smoothing and Knowledge Distillation—0
On the Convergence of Nonconvex Continual Learning with Adaptive Learning Rate—0
When in Doubt, Summon the Titans: A Framework for Efficient Inference with Large Models—0
Towards Unknown-aware Learning with Virtual Outlier Synthesis—0
Dataset Bias Prediction for Few-Shot Image Classification—0
Image BERT Pre-training with Online Tokenizer—0
How to Adapt Your Large-Scale Vision-and-Language Model—0
HFSP: A Hardware-friendly Soft Pruning Framework for Vision Transformers—0
Cross Domain Ensemble Distillation for Domain Generalization—0
Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing—0
Towards Generic Interface for Human-Neural Network Knowledge Exchange—0
Does deep learning model calibration improve performance in class-imbalanced medical image classification?—0
Combining Human Predictions with Model Probabilities via Confusion Matrices and CalibrationCode1
Second-Order Neural ODE OptimizerCode1
Robust Temporal Ensembling for Learning with Noisy Labels—0
Chest X-Rays Image Classification from beta-Variational Autoencoders Latent Features—0
Segmentation of Roads in Satellite Images using specially modified U-Net CNNs—0
UFO-ViT: High Performance Linear Vision Transformer without SoftmaxCode0
Improvising the Learning of Neural Networks on Hyperspherical ManifoldCode0
Multi-loss ensemble deep learning for chest X-ray classification—0
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition—0
Which Design Decisions in AI-enabled Mobile Applications Contribute to Greener AI?—0
A Contrastive Learning Approach to Auroral Identification and Classification—0
Evaluation of Deep Neural Network Domain Adaptation Techniques for Image RecognitionCode1
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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