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 3801–3850 of 10420 papers

TitleStatusHype
BFO Meets HOG: Feature Extraction Based on Histograms of Oriented p.d.f. Gradients for Image Classification—0
Detection Booster Training: A detection booster training method for improving the accuracy of classifiers.—0
Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning—0
Explanation of Unintended Radiated Emission Classification via LIME—0
Explanations for Automatic Speech Recognition—0
Explanations of Classifiers Enhance Medical Image Segmentation via End-to-end Pre-training—0
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications—0
Generalisation First, Memorisation Second? Memorisation Localisation for Natural Language Classification Tasks—0
Explicit Connection Distillation—0
Explicit Domain Adaptation with Loosely Coupled Samples—0
Explicitly Modeled Attention Maps for Image Classification—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
Detecting Visually Relevant Sentences for Fine-Grained Classification—0
Exploiting Category Names for Few-Shot Classification with Vision-Language Models—0
Exploiting Contextual Uncertainty of Visual Data for Efficient Training of Deep Models—0
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification—0
BFBox: Searching Face-Appropriate Backbone and Feature Pyramid Network for Face Detector—0
Exploiting Kernel Compression on BNNs—0
Detecting Spurious Correlations via Robust Visual Concepts in Real and AI-Generated Image Classification—0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
Exploiting Local Features from Deep Networks for Image Retrieval—0
Exploiting Nontrivial Connectivity for Automatic Speech Recognition—0
An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants—0
Gemini Pro Defeated by GPT-4V: Evidence from Education—0
Detecting Overfitting via Adversarial Examples—0
Exploiting Web Images for Dataset Construction: A Domain Robust Approach—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
Exploration of Multi-Scale Image Fusion Systems in Intelligent Medical Image Analysis—0
Exploration of Noise Strategies in Semi-supervised Named Entity Classification—0
Explore the Effect of Data Selection on Poison Efficiency in Backdoor Attacks—0
An Analysis of Pre-Training on Object Detection—0
Explore the Power of Dropout on Few-shot Learning—0
Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability—0
CoLa-DCE -- Concept-guided Latent Diffusion Counterfactual Explanations—0
Exploring Camera Encoder Designs for Autonomous Driving Perception—0
Exploring Category-correlated Feature for Few-shot Image Classification—0
Exploring Cross-Domain Pretrained Model for Hyperspectral Image Classification—0
Exploring Data Augmentations on Self-/Semi-/Fully- Supervised Pre-trained Models—0
AdaScale SGD: A Scale-Invariant Algorithm for Distributed Training—0
Exploring Deep Learning Methods for Classification of SAR Images: Towards NextGen Convolutions via Transformers—0
Exploring Effects of Hyperdimensional Vectors for Tsetlin Machines—0
Exploring Emerging Trends and Research Opportunities in Visual Place Recognition—0
Detecting Novelties with Empty Classes—0
Exploring Explainability Methods for Graph Neural Networks—0
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis—0
Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models—0
Exploring Feature Reuse in DenseNet Architectures—0
Collage Inference: Using Coded Redundancy for Low Variance Distributed Image Classification—0
Beyond the Visible: Multispectral Vision-Language Learning for Earth Observation—0
AHA! an 'Artificial Hippocampal Algorithm' for Episodic Machine 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