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 5451–5500 of 10420 papers

TitleStatusHype
KAN-Mixers: a new deep learning architecture for image classification—0
Batch Kalman Normalization: Towards Training Deep Neural Networks with Micro-Batches—0
KANs for Computer Vision: An Experimental Study—0
Cross-Hierarchical Bidirectional Consistency Learning for Fine-Grained Visual Classification—0
Deep Neural Network Models Trained With A Fixed Random Classifier Transfer Better Across Domains—0
KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization—0
AI of Brain and Cognitive Sciences: From the Perspective of First Principles—0
Keeping Representation Similarity in Finetuning for Medical Image Analysis—0
Learning to Learn Image Classifiers with Visual Analogy—0
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine—0
Keep Your AI-es on the Road: Tackling Distracted Driver Detection with Convolutional Neural Networks and Targeted Data Augmentation—0
Keep your distance: learning dispersed embeddings on S_m—0
Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification—0
AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods—0
Deep Neural Networks for Object Detection—0
Kernel Descriptors for Visual Recognition—0
Deep Neural Networks for Pattern Recognition—0
Kernel Extreme Learning Machine Optimized by the Sparrow Search Algorithm for Hyperspectral Image Classification—0
Heterogeneous Generative Knowledge Distillation with Masked Image Modeling—0
Deep Neural Networks Fused with Textures for Image Classification—0
Heterogeneous Federated Learning Using Knowledge Codistillation—0
Kernel Methods in Hyperbolic Spaces—0
Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification—0
Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders—0
Kernel principal component analysis network for image classification—0
Kernel Reconstruction ICA for Sparse Representation—0
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis—0
Cross-filter compression for CNN inference acceleration—0
Hermitry Ratio: Evaluating the validity of perturbation methods for explainable deep learning—0
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning—0
Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense—0
Cross-Domain Sparse Coding—0
Semantic-Aware Contrastive Learning for Multi-object Medical Image Segmentation—0
Knee or ROC—0
Learning to generate imaginary tasks for improving generalization in meta-learning—0
Learning to predict visual brain activity by predicting future sensory states—0
HEp-2 Cell Image Classification with Deep Convolutional Neural Networks—0
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models—0
Knowledge Concentration: Learning 100K Object Classifiers in a Single CNN—0
Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach—0
Learning to Detect Malicious Clients for Robust Federated Learning—0
Learning to Detect Semantic Boundaries with Image-level Class Labels—0
Knowledge Distillation for Incremental Learning in Semantic Segmentation—0
Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation—0
HDF: Hybrid Deep Features for Scene Image Representation—0
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition—0
Knowledge Distillation in Generations: More Tolerant Teachers Educate Better Students—0
Knowledge Distillation in Vision Transformers: A Critical Review—0
Have Large Vision-Language Models Mastered Art History?—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