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

Showing 40514075 of 10420 papers

TitleStatusHype
Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural NetworkCode0
Tuned Compositional Feature Replays for Efficient Stream LearningCode0
I Bet You Did Not Mean That: Testing Semantic Importance via BettingCode0
IDEA: Image Description Enhanced CLIP-AdapterCode0
Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNNCode0
Hyperspectral Image Classification in the Presence of Noisy LabelsCode0
Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape AnalysisCode0
Hyperparameter Ensembles for Robustness and Uncertainty QuantificationCode0
Cross-Modal Alternating Learning with Task-Aware Representations for Continual LearningCode0
HyperDID: Hyperspectral Intrinsic Image Decomposition with Deep Feature EmbeddingCode0
Federated Unlearning Made Practical: Seamless Integration via Negated Pseudo-GradientsCode0
Federated Unlearning via Class-Discriminative PruningCode0
Hyperspectral Image Classification via Transformer-based Spectral-Spatial Attention Decoupling and Adaptive GatingCode0
Attention Masks Help Adversarial Attacks to Bypass Safety DetectorsCode0
HyperbolicLR: Epoch insensitive learning rate schedulerCode0
HyenaPixel: Global Image Context with ConvolutionsCode0
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural NetworksCode0
HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image ClassificationCode0
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical ProjectionsCode0
Hyperspectral image classification via a random patches networkCode0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
Cross-domain Open-world DiscoveryCode0
Cross-Domain Image Classification through Neural-Style Transfer Data AugmentationCode0
The Effectiveness of Data Augmentation in Image Classification using Deep LearningCode0
Feature Extractor Stacking for Cross-domain Few-shot LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified