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 4626–4650 of 10420 papers

TitleStatusHype
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