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 6551–6600 of 10420 papers

TitleStatusHype
Fuzzy Rank-based Fusion of CNN Models using Gompertz Function for Screening COVID-19 CT-ScansCode0
Federated Model Search via Reinforcement Learning—0
Federated Learning with Downlink Device Selection—0
Introducing the structural bases of typicality effects in deep learning—0
Understanding Intrinsic Robustness Using Label UncertaintyCode0
Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillation—0
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps—0
Generalization Error Analysis of Neural networks with Gradient Based Regularization—0
Confidence-based Out-of-Distribution Detection: A Comparative Study and AnalysisCode0
Continual Contrastive Learning for Image ClassificationCode0
Exact Backpropagation in Binary Weighted Networks with Group Weight TransformationsCode0
MMF: Multi-Task Multi-Structure Fusion for Hierarchical Image Classification—0
Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning—0
Magnification-independent Histopathological Image Classification with Similarity-based Multi-scale EmbeddingsCode0
Towards Measuring Bias in Image Classification—0
On the Practicality of Deterministic Epistemic UncertaintyCode0
Temporally Sorting Images from Real-World EventsCode0
Overhead-MNIST: Machine Learning Baselines for Image Classification—0
Exploring Robust Architectures for Deep Artificial Neural NetworksCode0
One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map—0
Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions—0
Exploring Localization for Self-supervised Fine-grained Contrastive Learning—0
Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image ClassificationCode0
Zoo-Tuning: Adaptive Transfer from a Zoo of Models—0
Adaptive Sample Selection for Robust Learning under Label NoiseCode0
Hyperspectral Remote Sensing Image Classification Based on Multi-scale Cross Graphic Convolution—0
Progressive Class-based Expansion Learning For Image Classification—0
Immuno-mimetic Deep Neural Networks (Immuno-Net)—0
Image Classification with CondenseNeXt for ARM-Based Computing PlatformsCode0
Scene Uncertainty and the Wellington Posterior of Deterministic Image Classifiers—0
Efficient Document Image Classification Using Region-Based Graph Neural Network—0
NN2CAM: Automated Neural Network Mapping for Multi-Precision Edge Processing on FPGA-Based Cameras—0
Frequency Domain Convolutional Neural Network: Accelerated CNN for Large Diabetic Retinopathy Image Classification—0
PatentNet: A Large-Scale Incomplete Multiview, Multimodal, Multilabel Industrial Goods Image Database—0
Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space—0
Classifying Textual Data with Pre-trained Vision Models through Transfer Learning and Data TransformationsCode0
Bayesian Statistics Guided Label Refurbishment Mechanism: Mitigating Label Noise in Medical Image ClassificationCode0
Florida Wildlife Camera Trap Dataset—0
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations—0
The Hitchhiker's Guide to Prior-Shift AdaptationCode0
Fourier Transform Approximation as an Auxiliary Task for Image ClassificationCode0
Adaptive Learning Rate and Momentum for Training Deep Neural NetworksCode0
Stochastic Polyak Stepsize with a Moving Target—0
TNT: Text-Conditioned Network with Transductive Inference for Few-Shot Video ClassificationCode0
Segmentation of cell-level anomalies in electroluminescence images of photovoltaic modules—0
Brain tumor grade classification Using LSTM Neural Networks with Domain Pre-Transforms—0
On fine-tuning of Autoencoders for Fuzzy rule classifiers—0
ImageNet Pre-training also Transfers Non-RobustnessCode0
Policy Smoothing for Provably Robust Reinforcement Learning—0
Communication Efficient SGD via Gradient Sampling With Bayes Prior—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