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 5001–5050 of 10420 papers

TitleStatusHype
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability—0
ImageNet MPEG-7 Visual Descriptors - Technical Report—0
It's Not a Modality Gap: Characterizing and Addressing the Contrastive Gap—0
A Tutorial on Explainable Image Classification for Dementia Stages Using Convolutional Neural Network and Gradient-weighted Class Activation Mapping—0
How do Hyenas deal with Human Speech? Speech Recognition and Translation with ConfHyena—0
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?—0
Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy—0
Image Recognition using Region Creep—0
Adversarial Rain Attack and Defensive Deraining for DNN Perception—0
J3DAI: A tiny DNN-Based Edge AI Accelerator for 3D-Stacked CMOS Image Sensor—0
How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance—0
Image Retrieval with Fisher Vectors of Binary Features—0
Image Segmentation Using Overlapping Group Sparsity—0
How Does Diverse Interpretability of Textual Prompts Impact Medical Vision-Language Zero-Shot Tasks?—0
Revisiting Classification Perspective on Scene Text Recognition—0
ImageTTR: Grounding Type Theory with Records in Image Classification for Visual Question Answering—0
How do Convolutional Neural Networks Learn Design?—0
IM: An R-Package for Computation of Image Moments and Moment Invariants—0
Imbalanced Classification in Medical Imaging via Regrouping—0
How Compact?: Assessing Compactness of Representations through Layer-Wise Pruning—0
Imbalanced Malware Images Classification: a CNN based Approach—0
StackMix: A complementary Mix algorithm—0
Adam^+: A Stochastic Method with Adaptive Variance Reduction—0
How adversarial attacks can disrupt seemingly stable accurate classifiers—0
IM-Loss: Information Maximization Loss for Spiking Neural Networks—0
Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks—0
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning—0
Immuno-mimetic Deep Neural Networks (Immuno-Net)—0
CSIT-Free Model Aggregation for Federated Edge Learning via Reconfigurable Intelligent Surface—0
Impact of Aliasing on Generalization in Deep Convolutional Networks—0
Impact of Attention on Adversarial Robustness of Image Classification Models—0
Impact of Automatic Image Classification and Blind Deconvolution in Improving Text Detection Performance of the CRAFT Algorithm—0
Impact of base dataset design on few-shot image classification—0
Impact of Batch Normalization on Convolutional Network Representations—0
Impact of Colour Variation on Robustness of Deep Neural Networks—0
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models—0
Impact of Data Normalization on Deep Neural Network for Time Series Forecasting—0
Impact of Feedback Type on Explanatory Interactive Learning—0
Attribute Recognition by Joint Recurrent Learning of Context and Correlation—0
Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models—0
Impact of Light and Shadow on Robustness of Deep Neural Networks—0
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks—0
Hierarchical Auxiliary Learning—0
Impact of Privacy Parameters on Deep Learning Models for Image Classification—0
Iterative Online Image Synthesis via Diffusion Model for Imbalanced Classification—0
Impact of Scaled Image on Robustness of Deep Neural Networks—0
Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control—0
Implementation of Artificial Neural Networks for the Nepta-Uranian Interplanetary (NUIP) Mission—0
Implementation of Deep Convolutional Neural Network in Multi-class Categorical Image Classification—0
CSIFT Based Locality-constrained Linear Coding for Image Classification—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