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

Showing 29262950 of 10420 papers

TitleStatusHype
Continual Learning with Strong Experience ReplayCode0
Efficient Multi-Scale Attention Module with Cross-Spatial LearningCode2
Impact of Light and Shadow on Robustness of Deep Neural Networks0
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design0
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained ModelsCode1
Detection of healthy and diseased crops in drone captured images using Deep LearningCode0
Digital-SC: Digital Semantic Communication with Adaptive Network Split and Learned Non-Linear Quantization0
Feasibility of Transfer Learning: A Mathematical Framework0
Uncertainty-based Detection of Adversarial Attacks in Semantic SegmentationCode0
Label Smarter, Not Harder: CleverLabel for Faster Annotation of Ambiguous Image Classification with Higher QualityCode0
Enhanced Meta Label Correction for Coping with Label CorruptionCode0
Mapping Biological Neuron Dynamics into an Interpretable Two-layer Artificial Neural Network0
WOT-Class: Weakly Supervised Open-world Text ClassificationCode0
Chest X-ray Image Classification: A Causal Perspective0
Revisiting 16-bit Neural Network Training: A Practical Approach for Resource-Limited LearningCode0
Skin Lesion Diagnosis Using Convolutional Neural Networks0
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional SettingsCode0
SPENSER: Towards a NeuroEvolutionary Approach for Convolutional Spiking Neural NetworksCode0
ONE-PEACE: Exploring One General Representation Model Toward Unlimited ModalitiesCode3
CageViT: Convolutional Activation Guided Efficient Vision Transformer0
Exploring the cloud of feature interaction scores in a Rashomon set0
Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence Uncertainties0
Transfer Learning for Fine-grained Classification Using Semi-supervised Learning and Visual Transformers0
Deep Learning Applications Based on WISE Infrared Data: Classification of Stars, Galaxies and Quasars0
Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural networkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified