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 3801–3850 of 10419 papers

TitleStatusHype
Distilled Gradual Pruning with Pruned Fine-tuningCode0
Hybrid CNN Bi-LSTM neural network for Hyperspectral image classification—0
Balancing the Causal Effects in Class-Incremental Learning—0
Investigation of Federated Learning Algorithms for Retinal Optical Coherence Tomography Image Classification with Statistical HeterogeneityCode0
How Flawed Is ECE? An Analysis via Logit SmoothingCode0
What to Do When Your Discrete Optimization Is the Size of a Neural Network?Code0
Reducing Texture Bias of Deep Neural Networks via Edge Enhancing DiffusionCode0
Comparing supervised learning dynamics: Deep neural networks match human data efficiency but show a generalisation lagCode0
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models—0
I can't see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption—0
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs—0
APALU: A Trainable, Adaptive Activation Function for Deep Learning Networks—0
Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging ClassificationCode0
Accuracy of TextFooler black box adversarial attacks on 01 loss sign activation neural network ensembleCode0
Contrastive Learning for Regression on Hyperspectral Data—0
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense—0
A novel spatial-frequency domain network for zero-shot incremental learning—0
Latent Enhancing AutoEncoder for Occluded Image Classification—0
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation—0
The SkipSponge Attack: Sponge Weight Poisoning of Deep Neural Networks—0
SAE: Single Architecture Ensemble Neural Networks—0
Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks—0
Feature Density Estimation for Out-of-Distribution Detection via Normalizing Flows—0
Adaptive Activation Functions for Predictive Modeling with Sparse Experimental DataCode0
A Bandit Approach with Evolutionary Operators for Model Selection—0
Multi-Scale Semantic Segmentation with Modified MBConv Blocks—0
Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning—0
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors—0
EVA-CLIP-18B: Scaling CLIP to 18 Billion ParametersCode0
A Lightweight Randomized Nonlinear Dictionary Learning Method using Random Vector Functional Link—0
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning—0
Pre-training of Lightweight Vision Transformers on Small Datasets with Minimally Scaled Images—0
Boosting Adversarial Transferability across Model Genus by Deformation-Constrained WarpingCode0
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate—0
Image-Caption Encoding for Improving Zero-Shot GeneralizationCode0
SynthVision - Harnessing Minimal Input for Maximal Output in Computer Vision Models using Synthetic Image data—0
DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision TransformersCode0
Foundation Model Makes Clustering A Better Initialization For Cold-Start Active LearningCode0
InceptionCapsule: Inception-Resnet and CapsuleNet with self-attention for medical image Classification—0
Déjà Vu Memorization in Vision-Language Models—0
CEPA: Consensus Embedded Perturbation for Agnostic Detection and Inversion of Backdoors—0
MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning—0
Faster Inference of Integer SWIN Transformer by Removing the GELU Activation—0
Segment Any Change—0
Direct side information learning for zero-shot regressionCode0
Deep Continuous NetworksCode0
Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics—0
CADICA: a new dataset for coronary artery disease detection by using invasive coronary angiography—0
Towards Physical Plausibility in Neuroevolution SystemsCode0
HyperZZW Operator Connects Slow-Fast Networks for Full Context InteractionCode0
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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