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 8776–8800 of 10420 papers

TitleStatusHype
Accelerating Training of Deep Neural Networks with a Standardization LossCode0
How transfer learning is used in generative models for image classification: improved accuracyCode0
DS_FusionNet: Dynamic Dual-Stream Fusion with Bidirectional Knowledge Distillation for Plant Disease RecognitionCode0
Accelerating Targeted Hard-Label Adversarial Attacks in Low-Query Black-Box SettingsCode0
DSD: Dense-Sparse-Dense Training for Deep Neural NetworksCode0
Drop to Adapt: Learning Discriminative Features for Unsupervised Domain AdaptationCode0
Dropout is NOT All You Need to Prevent Gradient LeakageCode0
DropBlock: A regularization method for convolutional networksCode0
Milking CowMask for Semi-Supervised Image ClassificationCode0
HSI-CNN: A Novel Convolution Neural Network for Hyperspectral ImageCode0
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave ConvolutionCode0
Out-of-distribution Detection by Cross-class Vicinity Distribution of In-distribution DataCode0
MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification ModelsCode0
Quantile-based Maximum Likelihood Training for Outlier DetectionCode0
Compressed Learning: A Deep Neural Network ApproachCode0
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-ArtCode0
Adaptive Sample Selection for Robust Learning under Label NoiseCode0
Robust and accelerated single-spike spiking neural network training with applicability to challenging temporal tasksCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
Out-of-distribution forgetting: vulnerability of continual learning to intra-class distribution shiftCode0
Improving Deep Neural Network Classification Confidence using Heatmap-based eXplainable AICode0
Human-imperceptible, Machine-recognizable ImagesCode0
Drop Clause: Enhancing Performance, Interpretability and Robustness of the Tsetlin MachineCode0
Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised LearningCode0
Human-in-the-Loop Visual Re-ID for Population Size EstimationCode0
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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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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