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

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Showing 9301–9350 of 10420 papers

TitleStatusHype
Free Performance Gain from Mixing Multiple Partially Labeled Samples in Multi-label Image Classification—0
Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training—0
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning—0
Frequency-Adaptive Discrete Cosine-ViT-ResNet Architecture for Sparse-Data Vision—0
Frequency Disentangled Residual Network—0
Frequency Domain Compact 3D Convolutional Neural Networks—0
Frequency Domain Convolutional Neural Network: Accelerated CNN for Large Diabetic Retinopathy Image Classification—0
Frequency Dropout: Feature-Level Regularization via Randomized Filtering—0
Frequency learning for image classification—0
Frequency Pooling: Shift-Equivalent and Anti-Aliasing Downsampling—0
From Artificial Intelligence to Brain Intelligence: The basis learning and memory algorithm for brain-like intelligence—0
From augmented microscopy to the topological transformer: a new approach in cell image analysis for Alzheimer's research—0
From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers—0
From Categories to Classifiers: Name-Only Continual Learning by Exploring the Web—0
From Categories to Subcategories: Large-Scale Image Classification With Partial Class Label Refinement—0
From Dictionary of Visual Words to Subspaces: Locality-Constrained Affine Subspace Coding—0
From images in the wild to video-informed image classification—0
From Image to Video: An Empirical Study of Diffusion Representations—0
From Information Bottleneck To Activation Norm Penalty—0
From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics—0
From Local Similarity to Global Coding: An Application to Image Classification—0
From Maxout to Channel-Out: Encoding Information on Sparse Pathways—0
From Online Behaviours to Images: A Novel Approach to Social Bot Detection—0
From pixels to planning: scale-free active inference—0
From visual words to a visual grammar: using language modelling for image classification—0
Frost filtered scale-invariant feature extraction and multilayer perceptron for hyperspectral image classification—0
Frozen Feature Augmentation for Few-Shot Image Classification—0
Efficient Online ML API Selection for Multi-Label Classification Tasks—0
Frugal Reinforcement-based Active Learning—0
Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction—0
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary—0
Full-attention based Neural Architecture Search using Context Auto-regression—0
Fully Connected Deep Structured Networks—0
Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features—0
Fully Hyperbolic Convolutional Neural Networks—0
Function-Space Regularization for Deep Bayesian Classification—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Fundamental Limits of Transfer Learning in Binary Classifications—0
FUNN: Flexible Unsupervised Neural Network—0
FUSECAPS: Investigating Feature Fusion Based Framework for Capsule Endoscopy Image Classification—0
Fusing Deep Convolutional Networks for Large Scale Visual Concept Classification—0
Fusion framework and multimodality for the Laplacian approximation of Bayesian neural networks—0
Fusion of Convolutional Neural Network and Statistical Features for Texture classification—0
Fusion of evidential CNN classifiers for image classification—0
Fusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification—0
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition—0
Fuzzy-Based Dialectical Non-Supervised Image Classification and Clustering—0
Fuzzy Pooling—0
Fuzzy Pooling—0
Fuzzy Rank-based Late Fusion Technique for Cytology image Segmentation—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