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 9501–9525 of 10420 papers

TitleStatusHype
Guiding the retraining of convolutional neural networks against adversarial inputs—0
GvT: A Graph-based Vision Transformer with Talking-Heads Utilizing Sparsity, Trained from Scratch on Small Datasets—0
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification—0
HAct: Out-of-Distribution Detection with Neural Net Activation Histograms—0
Half-CNN: A General Framework for Whole-Image Regression—0
Hallucinating Saliency Maps for Fine-Grained Image Classification for Limited Data Domains—0
HAMIL: Hierarchical Aggregation-Based Multi-Instance Learning for Microscopy Image Classification—0
Handwritten digit and letter recognition using hybrid dwt-dct with knn and svm classifier—0
FEATHERS: Federated Architecture and Hyperparameter Search—0
HAO: Hardware-aware neural Architecture Optimization for Efficient Inference—0
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples—0
Hardware Architecture of Embedded Inference Accelerator and Analysis of Algorithms for Depthwise and Large-Kernel Convolutions—0
Hardware/Software Co-Design of RISC-V Extensions for Accelerating Sparse DNNs on FPGAs—0
Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks—0
Harnessing Increased Client Participation with Cohort-Parallel Federated Learning—0
Harnessing The Power of Attention For Patch-Based Biomedical Image Classification—0
Harvesting Mid-level Visual Concepts from Large-Scale Internet Images—0
HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images—0
HASeparator: Hyperplane-Assisted Softmax—0
Hashing on Nonlinear Manifolds—0
Have Large Vision-Language Models Mastered Art History?—0
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition—0
HDF: Hybrid Deep Features for Scene Image Representation—0
HEp-2 Cell Image Classification with Deep Convolutional Neural Networks—0
Hermitry Ratio: Evaluating the validity of perturbation methods for explainable deep 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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified