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

Showing 23512375 of 10420 papers

TitleStatusHype
Are Straight-Through gradients and Soft-Thresholding all you need for Sparse Training?Code0
PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and HumansCode0
Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image ClassificationCode0
A Group-Theoretic Framework for Data AugmentationCode0
Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-raysCode0
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)Code0
ADVISE: ADaptive Feature Relevance and VISual Explanations for Convolutional Neural NetworksCode0
Enhancing Self-Supervised Learning for Remote Sensing with Elevation Data: A Case Study with Scarce And High Level Semantic LabelsCode0
Interlocking Backpropagation: Improving depthwise model-parallelismCode0
InterpNET: Neural Introspection for Interpretable Deep LearningCode0
Invariant backpropagation: how to train a transformation-invariant neural networkCode0
ISyNet: Convolutional Neural Networks design for AI acceleratorCode0
Are LSTMs Good Few-Shot Learners?Code0
Instilling Inductive Biases with SubnetworksCode0
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image ClassificationCode0
Intelligent Multi-View Test Time AugmentationCode0
Instance-dependent Label Distribution Estimation for Learning with Label NoiseCode0
Instance Enhancement Batch Normalization: an Adaptive Regulator of Batch NoiseCode0
Instance Temperature Knowledge DistillationCode0
An Intelligent Remote Sensing Image Quality Inspection SystemCode0
Input-gradient space particle inference for neural network ensemblesCode0
Combined Depth Space based Architecture Search For Person Re-identificationCode0
Input Invex Neural NetworkCode0
Initialization Matters for Adversarial Transfer LearningCode0
In-Place Activated BatchNorm for Memory-Optimized Training of DNNsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified