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 5601–5625 of 10420 papers

TitleStatusHype
Calibrating Histopathology Image Classifiers using Label Smoothing—0
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning—0
DropKey for Vision Transformer—0
DropKey—0
DropFilter: A Novel Regularization Method for Learning Convolutional Neural Networks—0
DRO-Augment Framework: Robustness by Synergizing Wasserstein Distributionally Robust Optimization and Data Augmentation—0
Drift to Remember—0
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification—0
An Extendable, Efficient and Effective Transformer-based Object Detector—0
A Domain Decomposition-Based CNN-DNN Architecture for Model Parallel Training Applied to Image Recognition Problems—0
A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging—0
Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error—0
CageViT: Convolutional Activation Guided Efficient Vision Transformer—0
DQA: An Efficient Method for Deep Quantization of Deep Neural Network Activations—0
CADICA: a new dataset for coronary artery disease detection by using invasive coronary angiography—0
An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration—0
DPSNN: A Differentially Private Spiking Neural Network with Temporal Enhanced Pooling—0
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization—0
DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures—0
CacheNet: A Model Caching Framework for Deep Learning Inference on the Edge—0
Admissibility of Stein Shrinkage for Batch Normalization in the Presence of Adversarial Attacks—0
C2S2: Cost-aware Channel Sparse Selection for Progressive Network Pruning—0
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild—0
C2G-Net: Exploiting Morphological Properties for Image Classification—0
A New Window Loss Function for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation—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