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 6851–6900 of 10420 papers

TitleStatusHype
QReLU and m-QReLU: Two novel quantum activation functions to aid medical diagnosticsCode1
Does Data Augmentation Benefit from Split BatchNorms—0
Layer-adaptive sparsity for the Magnitude-based PruningCode1
LiteDepthwiseNet: An Extreme Lightweight Network for Hyperspectral Image Classification—0
Self-Supervised Domain Adaptation with Consistency TrainingCode1
Improved Multi-Source Domain Adaptation by Preservation of Factors—0
HS-ResNet: Hierarchical-Split Block on Convolutional Neural NetworkCode1
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed GradientsCode2
Ferrograph image classification—0
Effects of the Nonlinearity in Activation Functions on the Performance of Deep Learning ModelsCode0
An Evasion Attack against Stacked Capsule AutoencoderCode0
Deep Ensembles for Low-Data Transfer Learning—0
Human-interpretable model explainability on high-dimensional data—0
Tensor Train Factorization and Completion under Noisy Data with Prior Analysis and Rank EstimationCode0
A Very Compact Embedded CNN Processor Design Based on Logarithmic Computing—0
Are all negatives created equal in contrastive instance discrimination?—0
Training independent subnetworks for robust predictionVerified1
Few-shot Action Recognition with Implicit Temporal Alignment and Pair Similarity Optimization—0
Robust Two-Stream Multi-Feature Network for Driver Drowsiness Detection—0
Satellite Image Classification with Deep Learning—0
RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification—0
Beyond the Attention: Distinguish the Discriminative and Confusable Features For Fine-grained Image Classification—0
Shape-Texture Debiased Neural Network TrainingCode1
CC-Loss: Channel Correlation Loss For Image Classification—0
Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers—0
Webly Supervised Image Classification with Metadata: Automatic Noisy Label Correction via Visual-Semantic GraphCode0
Open-sourced Dataset Protection via Backdoor WatermarkingCode1
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray ModelsCode1
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image ClassificationCode1
ByzShield: An Efficient and Robust System for Distributed TrainingCode0
Block-term Tensor Neural Networks—0
Regularizing Neural Networks via Adversarial Model PerturbationCode1
Brain-inspired predictive coding dynamics improve the robustness of deep neural networksCode0
Understanding Local Robustness of Deep Neural Networks under Natural VariationsCode0
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization—0
Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image ClassificationCode1
A Novel ANN Structure for Image Recognition—0
Uncertainty-Aware Few-Shot Image Classification—0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
R-MnasNet: Reduced MnasNet for Computer Vision—0
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks—0
A Fully Tensorized Recurrent Neural NetworkCode1
Interlocking Backpropagation: Improving depthwise model-parallelismCode0
From Artificial Intelligence to Brain Intelligence: The basis learning and memory algorithm for brain-like intelligence—0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images—0
Conversion and Implementation of State-of-the-Art Deep Learning Algorithms for the Classification of Diabetic Retinopathy—0
SLCRF: Subspace Learning with Conditional Random Field for Hyperspectral Image Classification—0
Learning Binary Semantic Embedding for Histology Image Classification and RetrievalCode1
Variational Feature Disentangling for Fine-Grained Few-Shot Classification—0
A Data Set and a Convolutional Model for Iconography Classification in PaintingsCode1
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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