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 2951–2975 of 10420 papers

TitleStatusHype
A New Distance Measure for Non-Identical Data with Application to Image Classification—0
ADINet: Attribute Driven Incremental Network for Retinal Image Classification—0
A Differential Game Theoretic Neural Optimizer for Training Residual Networks—0
Building Human-like Communicative Intelligence: A Grounded Perspective—0
Building Efficient Lightweight CNN Models—0
A New Deep Neural Architecture Search Pipeline for Face Recognition—0
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach—0
Building extraction with vision transformer—0
A new dataset of dog breed images and a benchmark for fine-grained classification—0
Ensembles of feedforward-designed convolutional neural networks—0
Equivariance with Learned Canonicalization Functions—0
Evaluating Capability of Deep Neural Networks for Image Classification via Information Plane—0
Buffer Zone based Defense against Adversarial Examples in Image Classification—0
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems—0
Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation—0
A New Convolutional Network-in-Network Structure and Its Applications in Skin Detection, Semantic Segmentation, and Artifact Reduction—0
BT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition—0
Enhancing Transformers Through Conditioned Embedded Tokens—0
Enrich the content of the image Using Context-Aware Copy Paste—0
A New Compensatory Genetic Algorithm-Based Method for Effective Compressed Multi-function Convolutional Neural Network Model Selection with Multi-Objective Optimization—0
Broad Adversarial Training with Data Augmentation in the Output Space—0
A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks—0
A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation—0
Ensemble learning of diffractive optical networks—0
ADFQ-ViT: Activation-Distribution-Friendly Post-Training Quantization for Vision Transformers—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
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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified