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 3401–3425 of 10420 papers

TitleStatusHype
CC-Loss: Channel Correlation Loss For Image Classification—0
Efficient and Flexible Method for Reducing Moderate-size Deep Neural Networks with Condensation—0
Differentiable Deep Clustering with Cluster Size Constraints—0
Efficient and Reliable Overlay Networks for Decentralized Federated Learning—0
Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach—0
Test-time Adaptation in the Dynamic World with Compound Domain Knowledge Management—0
Differentiable Channel Sparsity Search via Weight Sharing within Filters—0
Anchor-based Nearest Class Mean Loss for Convolutional Neural Networks—0
Differentiable Architecture Compression—0
L_2BN: Enhancing Batch Normalization by Equalizing the L_2 Norms of Features—0
Bio-inspired learnable divisive normalization for ANNs—0
Efficient CNNs via Passive Filter Pruning—0
Efficient Computation of Quantized Neural Networks by −1, +1 Encoding Decomposition—0
Efficient Converted Spiking Neural Network for 3D and 2D Classification—0
A Closer Look at Personalization in Federated Image Classification—0
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models—0
Feature-based Graph Attention Networks Improve Online Continual Learning—0
DiffCLIP: Leveraging Stable Diffusion for Language Grounded 3D Classification—0
Efficient Deep Representation Learning by Adaptive Latent Space Sampling—0
An OpenCL(TM) Deep Learning Accelerator on Arria 10—0
Bin-wise Temperature Scaling (BTS): Improvement in Confidence Calibration Performance through Simple Scaling Techniques—0
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks—0
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks—0
BinImg2Vec: Augmenting Malware Binary Image Classification with Data2Vec—0
AdderSR: Towards Energy Efficient Image Super-Resolution—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