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 9126–9150 of 10420 papers

TitleStatusHype
Fast Adaptation with Linearized Neural Networks—0
Fast and Accurate Inference with Adaptive Ensemble Prediction for Deep Networks—0
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition—0
Fast and Efficient Information Transmission with Burst Spikes in Deep Spiking Neural Networks—0
Fast, Better Training Trick --- Random Gradient—0
Real-time Chest X-Ray Distributed Decision Support for Resource-constrained Clinics—0
Fast-DENSER++: Evolving Fully-Trained Deep Artificial Neural Networks—0
Faster Adaptive Federated Learning—0
Faster and Accurate Classification for JPEG2000 Compressed Images in Networked Applications—0
Faster Inference of Integer SWIN Transformer by Removing the GELU Activation—0
Faster Training by Selecting Samples Using Embeddings—0
Fast Fine-grained Image Classification via Weakly Supervised Discriminative Localization—0
Fast Fourier Convolution Based Remote Sensor Image Object Detection for Earth Observation—0
Fast Image Classification by Boosting Fuzzy Classifiers—0
Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks—0
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification—0
Fast Neural Architecture Construction using EnvelopeNets—0
FAST OBJECT LOCALIZATION VIA SENSITIVITY ANALYSIS—0
Fast Parametric Learning with Activation Memorization—0
Fast-ParC: Capturing Position Aware Global Feature for ConvNets and ViTs—0
FATNN: Fast and Accurate Ternary Neural Networks—0
FAT: Training Neural Networks for Reliable Inference Under Hardware Faults—0
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run—0
Feasibility of Transfer Learning: A Mathematical Framework—0
Feature Activation Map: Visual Explanation of Deep Learning Models for Image Classification—0
Show:102550
← PrevPage 366 of 417Next →
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