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 36763700 of 10420 papers

TitleStatusHype
Decoupled Greedy Learning of CNNsCode0
ImageNet Classification with Deep Convolutional Neural NetworksCode0
Soft ascent-descent as a stable and flexible alternative to floodingCode0
Decompose-and-Compose: A Compositional Approach to Mitigating Spurious CorrelationCode0
Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion modelsCode0
Image Classification with Hierarchical Multigraph NetworksCode0
Image Classification with Classic and Deep Learning TechniquesCode0
Automated wildlife image classification: An active learning tool for ecological applicationsCode0
Decision-making and control with diffractive optical networksCode0
Evaluating Generalization Ability of Convolutional Neural Networks and Capsule Networks for Image Classification via Top-2 ClassificationCode0
Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural networkCode0
Image Classification with CondenseNeXt for ARM-Based Computing PlatformsCode0
Decision Forests, Convolutional Networks and the Models in-BetweenCode0
Evaluating ResNeXt Model Architecture for Image ClassificationCode0
Evaluating Supervision Levels Trade-Offs for Infrared-Based People CountingCode0
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
Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays OffCode0
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
Image classification in frequency domain with 2SReLU: a second harmonics superposition activation functionCode0
Image-Caption Encoding for Improving Zero-Shot GeneralizationCode0
Image classification and retrieval with random depthwise signed convolutional neural networksCode0
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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