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

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Showing 8251–8300 of 10420 papers

TitleStatusHype
Effect of Superpixel Aggregation on Explanations in LIME -- A Case Study with Biological DataCode0
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost—0
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms—0
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design—0
Optimizing Convolutional Neural Networks for Embedded Systems by Means of Neuroevolution—0
Transfer Learning for Algorithm Recommendation—0
Scale-Equivariant Steerable NetworksCode0
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural NetworksCode0
Generative Image Translation for Data Augmentation in Colorectal Histopathology ImagesCode0
A CNN-RNN Framework for Image Annotation from Visual Cues and Social Network Metadata—0
Drop to Adapt: Learning Discriminative Features for Unsupervised Domain AdaptationCode0
Cross-Domain Image Classification through Neural-Style Transfer Data AugmentationCode0
Context-Gated ConvolutionCode0
Blink: Fast and Generic Collectives for Distributed ML—0
Demon: Improved Neural Network Training with Momentum DecayCode0
The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos?—0
Multi-Stage Pathological Image Classification using Semantic Segmentation—0
On the adequacy of untuned warmup for adaptive optimizationCode0
Cribriform pattern detection in prostate histopathological images using deep learning models—0
Observer Dependent Lossy Image CompressionCode0
Dynamic Mode Decomposition based feature for Image ClassificationCode0
Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces—0
Deep Kernel Learning via Random Fourier Features—0
Deformable Kernels: Adapting Effective Receptive Fields for Object DeformationCode0
Deep Neural Network Compression for Image Classification and Object DetectionCode0
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction MethodCode0
Distributed Learning of Deep Neural Networks using Independent Subnet TrainingCode0
Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image ClassificationCode0
Tensor-based algorithms for image classificationCode0
SELF: Learning to Filter Noisy Labels with Self-Ensembling—0
Training Multiscale-CNN for Large Microscopy Image Classification in One Hour—0
A General Upper Bound for Unsupervised Domain Adaptation—0
BUZz: BUffer Zones for defending adversarial examples in image classification—0
Harnessing the Power of Infinitely Wide Deep Nets on Small-data TasksCode0
Generalization Bounds for Convolutional Neural Networks—0
An empirical study of pretrained representations for few-shot classification—0
Contextual Local Explanation for Black Box Classifiers—0
Adversarially Robust Few-Shot Learning: A Meta-Learning ApproachCode0
W-Net: A CNN-based Architecture for White Blood Cells Image ClassificationCode0
Scalable Verified Training for Provably Robust Image Classification—0
A Large-scale Study of Representation Learning with the Visual Task Adaptation BenchmarkCode0
Siamese Networks: The Tale of Two Manifolds—0
SlowMo: Improving Communication-Efficient Distributed SGD with Slow MomentumCode0
Augmenting learning using symmetry in a biologically-inspired domain—0
Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence—0
A Weakly Supervised Fine Label Classifier Enhanced by Coarse Supervision—0
Leveraging Model Interpretability and Stability to increase Model RobustnessCode0
Auto-FPN: Automatic Network Architecture Adaptation for Object Detection Beyond Classification—0
AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos—0
DANet: Divergent Activation for Weakly Supervised Object LocalizationCode0
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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