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 3426–3450 of 10420 papers

TitleStatusHype
Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning—0
TransMed: Large Language Models Enhance Vision Transformer for Biomedical Image Classification—0
Efficient Few-Shot Medical Image Analysis via Hierarchical Contrastive Vision-Language Learning—0
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks—0
Efficient Fully Distributed Federated Learning with Adaptive Local Links—0
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks—0
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks—0
BinImg2Vec: Augmenting Malware Binary Image Classification with Data2Vec—0
Centroid Transformers: Learning to Abstract with Attention—0
Efficient Hyperparameter Importance Assessment for CNNs—0
Agnostic Multi-Robust Learning Using ERM—0
AdderSR: Towards Energy Efficient Image Super-Resolution—0
Efficient Key-Based Adversarial Defense for ImageNet by Using Pre-trained Model—0
DIET-SNN: A Low-Latency Spiking Neural Network with Direct Input Encoding & Leakage and Threshold Optimization—0
Efficient Lung Cancer Image Classification and Segmentation Algorithm Based on Improved Swin Transformer—0
Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework—0
Efficient Masked Autoencoders with Self-Consistency—0
Efficient Maximal Coding Rate Reduction by Variational Forms—0
Efficient Model-Agnostic Multi-Group Equivariant Networks—0
2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips—0
Efficient Model Performance Estimation via Feature Histories—0
AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray—0
Feature-level augmentation to improve robustness of deep neural networks to affine transformations—0
Feature Losses for Adversarial Robustness—0
Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning—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