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 4926–4950 of 10420 papers

TitleStatusHype
Exploiting the relationship between visual and textual features in social networks for image classification with zero-shot deep learning—0
Exploiting the Full Capacity of Deep Neural Networks while Avoiding Overfitting by Targeted Sparsity Regularization—0
Exploiting Patch Sizes and Resolutions for Multi-Scale Deep Learning in Mammogram Image Classification—0
A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations—0
Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons—0
Exploiting Nontrivial Connectivity for Automatic Speech Recognition—0
Exploiting Local Features from Deep Networks for Image Retrieval—0
Exploiting LMM-based knowledge for image classification tasks—0
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks—0
Exploiting Kernel Compression on BNNs—0
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification—0
Exploiting Contextual Uncertainty of Visual Data for Efficient Training of Deep Models—0
COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation—0
A Progressive Framework of Vision-language Knowledge Distillation and Alignment for Multilingual Scene—0
Exploiting Category Names for Few-Shot Classification with Vision-Language Models—0
Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs—0
Explicitly Modeled Attention Maps for Image Classification—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
Explicit Domain Adaptation with Loosely Coupled Samples—0
Explicit Connection Distillation—0
Coarse to Fine: Multi-label Image Classification with Global/Local Attention—0
Explanatory Masks for Neural Network Interpretability—0
CoAPT: Context Attribute words for Prompt Tuning—0
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images—0
Adversarial Robustness Assessment of NeuroEvolution Approaches—0
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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