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 3701–3750 of 10419 papers

TitleStatusHype
Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image ClassificationCode0
Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time DetectionCode0
Decompose-and-Compose: A Compositional Approach to Mitigating Spurious CorrelationCode0
Impact of Fully Connected Layers on Performance of Convolutional Neural Networks for Image ClassificationCode0
Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion modelsCode0
Comparing supervised learning dynamics: Deep neural networks match human data efficiency but show a generalisation lagCode0
Immiscible Color Flows in Optimal Transport Networks for Image ClassificationCode0
Impact of ImageNet Model Selection on Domain AdaptationCode0
Automated wildlife image classification: An active learning tool for ecological applicationsCode0
Decision-making and control with diffractive optical networksCode0
Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural networkCode0
iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-MixerCode0
Implicit Generative Prior for Bayesian Neural NetworksCode0
Decision Forests, Convolutional Networks and the Models in-BetweenCode0
DecisioNet: A Binary-Tree Structured Neural NetworkCode0
Automated Seed Quality Testing System using GAN & Active LearningCode0
Automated Search for Configurations of Deep Neural Network ArchitecturesCode0
DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and ExplanationCode0
Allowing humans to interactively guide machines where to look does not always improve human-AI team's classification accuracyCode0
Policy-Based Federated LearningCode0
ImageNot: A contrast with ImageNet preserves model rankingsCode0
Evolutionary NAS with Gene Expression Programming of Cellular EncodingCode0
ImageNet Classification with Deep Convolutional Neural NetworksCode0
Image Quality Assessment Guided Deep Neural Networks TrainingCode0
Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling CurvesCode0
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuseCode0
Demon: Improved Neural Network Training with Momentum DecayCode0
Automated Knowledge Distillation via Monte Carlo Tree SearchCode0
Adaptive Adversarial Cross-Entropy Loss for Sharpness-Aware MinimizationCode0
Image Classification with CondenseNeXt for ARM-Based Computing PlatformsCode0
Image Classification with Hierarchical Multigraph NetworksCode0
Image classification in frequency domain with 2SReLU: a second harmonics superposition activation functionCode0
Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network EnsembleCode0
Image Classification Using Singular Value Decomposition and OptimizationCode0
DDI-CoCo: A Dataset For Understanding The Effect Of Color Contrast In Machine-Assisted Skin Disease DetectionCode0
DDA: Dimensionality Driven Augmentation Search for Contrastive Learning in Laparoscopic SurgeryCode0
Evolving Deep Neural Networks by Multi-objective Particle Swarm Optimization for Image ClassificationCode0
Image-Caption Encoding for Improving Zero-Shot GeneralizationCode0
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene ClassificationCode0
Image classification and retrieval with random depthwise signed convolutional neural networksCode0
Image Classification with Classic and Deep Learning TechniquesCode0
Soft ascent-descent as a stable and flexible alternative to floodingCode0
Improving Generalization of Batch Whitening by Convolutional Unit OptimizationCode0
Identifying Transients in the Dark Energy Survey using Convolutional Neural NetworksCode0
Distilling Effective Supervision from Severe Label NoiseCode0
AutoGAN: Neural Architecture Search for Generative Adversarial NetworksCode0
DCFNet: Deep Neural Network with Decomposed Convolutional FiltersCode0
Identifying Adversarially Attackable and Robust SamplesCode0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
Saccader: Improving Accuracy of Hard Attention Models for VisionCode0
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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