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 4601–4650 of 10420 papers

TitleStatusHype
Making Vision Transformers Truly Shift-Equivariant—0
Triplet Knowledge Distillation—0
Batch Model Consolidation: A Multi-Task Model Consolidation FrameworkCode0
Superpixelwise Low-Rank Approximation-Based Partial Label Learning for Hyperspectral Image ClassificationCode0
Image as First-Order Norm+Linear Autoregression: Unveiling Mathematical Invariance—0
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual LearningCode0
Dual Path Transformer with Partition Attention—0
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical ImagingCode0
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning—0
Frequency maps reveal the correlation between Adversarial Attacks and Implicit BiasCode0
NOVUM: Neural Object Volumes for Robust Object ClassificationCode0
SUVR: A Search-based Approach to Unsupervised Visual Representation Learning—0
Federated Variational Inference: Towards Improved Personalization and Generalization—0
Impact of Light and Shadow on Robustness of Deep Neural Networks—0
Enhancing Accuracy and Robustness through Adversarial Training in Class Incremental Continual Learning—0
Sorted Convolutional Network for Achieving Continuous Rotational Invariance—0
Continual Learning with Strong Experience ReplayCode0
Feasibility of Transfer Learning: A Mathematical Framework—0
Uncertainty-based Detection of Adversarial Attacks in Semantic SegmentationCode0
Enhanced Meta Label Correction for Coping with Label CorruptionCode0
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 Quantization—0
Label Smarter, Not Harder: CleverLabel for Faster Annotation of Ambiguous Image Classification with Higher QualityCode0
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design—0
WOT-Class: Weakly Supervised Open-world Text ClassificationCode0
Mapping Biological Neuron Dynamics into an Interpretable Two-layer Artificial Neural Network—0
Chest X-ray Image Classification: A Causal Perspective—0
SPENSER: Towards a NeuroEvolutionary Approach for Convolutional Spiking Neural NetworksCode0
Revisiting 16-bit Neural Network Training: A Practical Approach for Resource-Limited LearningCode0
Skin Lesion Diagnosis Using Convolutional Neural Networks—0
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional SettingsCode0
Exploring the cloud of feature interaction scores in a Rashomon set—0
CageViT: Convolutional Activation Guided Efficient Vision Transformer—0
Deep Learning Applications Based on WISE Infrared Data: Classification of Stars, Galaxies and Quasars—0
Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural networkCode0
Transfer Learning for Fine-grained Classification Using Semi-supervised Learning and Visual Transformers—0
Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence Uncertainties—0
One-Shot Online Testing of Deep Neural Networks Based on Distribution Shift Detection—0
Learning More Discriminative Local Descriptors for Few-shot Learning—0
Predictive Models from Quantum Computer Benchmarks—0
Enhancing Performance of Vision Transformers on Small Datasets through Local Inductive Bias Incorporation—0
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks—0
Causal Analysis for Robust Interpretability of Neural Networks—0
SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification—0
Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity—0
Two-in-One: A Model Hijacking Attack Against Text Generation Models—0
Saturated Non-Monotonic Activation Functions—0
Meta-Optimization for Higher Model Generalizability in Single-Image Depth Prediction—0
To transfer or not transfer: Unified transferability metric and analysis—0
Feature Channel Adaptive Enhancement for Fine-Grained Visual Classification—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