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 7151–7200 of 10420 papers

TitleStatusHype
MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings—0
Deep Learning Based Brain Tumor Segmentation: A SurveyCode1
Robust Image Classification Using A Low-Pass Activation Function and DCT AugmentationCode0
OnlineAugment: Online Data Augmentation with Less Domain KnowledgeCode1
Improving Object Detection with Selective Self-supervised Self-training—0
Partial local entropy and anisotropy in deep weight spaces—0
Prioritized Multi-Criteria Federated Learning—0
A Differential Game Theoretic Neural Optimizer for Training Residual Networks—0
Impact of base dataset design on few-shot image classification—0
A Technical Report for VIPriors Image Classification Challenge—0
Generative Pretraining from PixelsCode2
OccamNet: A Fast Neural Model for Symbolic Regression at ScaleCode1
Unsupervised machine learning via transfer learning and k-means clustering to classify materials image dataCode1
On Robustness and Transferability of Convolutional Neural NetworksCode1
Advances in Deep Learning for Hyperspectral Image Analysis--Addressing Challenges Arising in Practical Imaging Scenarios—0
Camera Bias in a Fine Grained Classification Task—0
Layer-Wise Adaptive Updating for Few-Shot Image Classification—0
HyperTune: Dynamic Hyperparameter Tuning For Efficient Distribution of DNN Training Over Heterogeneous Systems—0
Data-Efficient Deep Learning Method for Image Classification Using Data Augmentation, Focal Cosine Loss, and EnsembleCode1
Focus-and-Expand: Training Guidance Through Gradual Manipulation of Input Features—0
Concept Learners for Few-Shot LearningCode1
AQD: Towards Accurate Fully-Quantized Object DetectionCode1
Pasadena: Perceptually Aware and Stealthy Adversarial Denoise Attack—0
Patch-wise Attack for Fooling Deep Neural NetworkCode1
Learning to Learn Parameterized Classification Networks for Scalable Input ImagesCode1
Learning and Exploiting Interclass Visual Correlations for Medical Image Classification—0
Adaptive Periodic Averaging: A Practical Approach to Reducing Communication in Distributed Learning—0
Temporal Self-Ensembling Teacher for Semi-Supervised Object DetectionCode1
Gravitational-wave selection effects using neural-network classifiersCode0
Entanglement and Tensor Networks for Supervised Image Classification—0
Locality Guided Neural Networks for Explainable Artificial Intelligence—0
VINNAS: Variational Inference-based Neural Network Architecture Search—0
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image ClassificationCode1
Distangling Biological Noise in Cellular Images with a focus on Explainability—0
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural NetworksCode1
The Computational Limits of Deep LearningCode0
EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision—0
Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma—0
Cautious Monotonicity in Case-Based Reasoning with Abstract Argumentation—0
Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks—0
Efficient detection of adversarial images—0
Maximum Entropy Regularization and Chinese Text Recognition—0
Learning to Reweight with Deep Interactions—0
AdaScale SGD: A User-Friendly Algorithm for Distributed TrainingCode1
StyPath: Style-Transfer Data Augmentation For Robust Histology Image ClassificationCode0
Attack of the Tails: Yes, You Really Can Backdoor Federated LearningCode1
Generalized Few-Shot Video Classification with Video Retrieval and Feature GenerationCode1
Dynamic Group Convolution for Accelerating Convolutional Neural NetworksCode1
AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks—0
Consistency Regularization with Generative Adversarial Networks for Semi-Supervised Learning—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