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 7401–7450 of 10420 papers

TitleStatusHype
BFBox: Searching Face-Appropriate Backbone and Feature Pyramid Network for Face Detector—0
Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration—0
Learning Augmentation Network via Influence Functions—0
Benchmarking Adversarial Robustness on Image ClassificationCode1
Weakly Supervised Fine-Grained Image Classification via Guassian Mixture Model Oriented Discriminative Learning—0
Rotation Consistent Margin Loss for Efficient Low-Bit Face Recognition—0
DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover's Distance and Structured Classifiers—0
Deep Degradation Prior for Low-Quality Image Classification—0
Attentive Weights Generation for Few Shot Learning via Information MaximizationCode1
Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations—0
GP-NAS: Gaussian Process Based Neural Architecture Search—0
Frequency Domain Compact 3D Convolutional Neural Networks—0
Fixed-Point Back-Propagation Training—0
Latent Domain Learning with Dynamic Residual Adapters—0
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements—0
Integrating global spatial features in CNN based Hyperspectral/SAR imagery classification—0
A Hierarchical Deep Convolutional Neural Network and Gated Recurrent Unit Framework for Structural Damage Detection—0
Towards Context-Agnostic Learning Using Synthetic DataCode0
Deep convolutional tensor networkCode1
ePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill IdentificationCode1
Overview: Computer vision and machine learning for microstructural characterization and analysis—0
Tensor decomposition to Compress Convolutional Layers in Deep LearningCode0
Fuzziness-based Spatial-Spectral Class Discriminant Information Preserving Active Learning for Hyperspectral Image ClassificationCode0
Balanced joint maximum mean discrepancy for deep transfer learningCode0
Explaining Neural Networks by Decoding Layer ActivationsCode0
Evolutionary NAS with Gene Expression Programming of Cellular EncodingCode0
On the Difficulty of Membership Inference AttacksCode1
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing FlowsCode0
SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference MeasureCode1
An Iteratively Optimized Patch Label Inference Network for Automatic Pavement Distress DetectionCode0
Accelerating Neural Network Inference by Overflow Aware Quantization—0
Generative Adversarial Networks for Bitcoin Data Augmentation—0
SCAN: Learning to Classify Images without LabelsCode2
Adaptive Adversarial Logits Pairing—0
An interpretable automated detection system for FISH-based HER2 oncogene amplification testing in histo-pathological routine images of breast and gastric cancer diagnosticsCode0
Hyperspectral Image Classification with Attention Aided CNNsCode1
Networks with pixels embedding: a method to improve noise resistance in images classificationCode0
Peri-Net-Pro: The neural processes with quantified uncertainty for crack patterns—0
One of these (Few) Things is Not Like the Others—0
SODA: Detecting Covid-19 in Chest X-rays with Semi-supervised Open Set Domain Adaptation—0
Semi-supervised Medical Image Classification with Global Latent MixingCode1
From ImageNet to Image Classification: Contextualizing Progress on BenchmarksCode1
Focus Longer to See Better:Recursively Refined Attention for Fine-Grained Image ClassificationCode1
HyperSTAR: Task-Aware Hyperparameters for Deep Networks—0
Conditionally Deep Hybrid Neural Networks Across Edge and Cloud—0
Perceptual Hashing applied to Tor domains recognition—0
Reducing Overlearning through Disentangled Representations by Suppressing Unknown TasksCode0
On Intrinsic Dataset Properties for Adversarial Machine LearningCode1
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural NetworksCode0
Improved Noisy Student Training for Automatic Speech RecognitionCode1
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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