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

Showing 91019125 of 10420 papers

TitleStatusHype
Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery0
Adversarial Learning of Label Dependency: A Novel Framework for Multi-class Classification0
A Smart System for Selection of Optimal Product Images in E-Commerce0
Fashion and Apparel Classification using Convolutional Neural Networks0
ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks0
Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles0
FLOPs as a Direct Optimization Objective for Learning Sparse Neural Networks0
Prototypical Clustering Networks for Dermatological Disease Diagnosis0
Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and BeyondCode0
DSNet: Deep and Shallow Feature Learning for Efficient Visual Tracking0
SparseFool: a few pixels make a big differenceCode0
Semantic bottleneck for computer vision tasks0
A Biologically Plausible Learning Rule for Deep Learning in the BrainCode0
FUNN: Flexible Unsupervised Neural Network0
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification0
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scaleCode0
Unauthorized AI cannot Recognize Me: Reversible Adversarial Example0
Introspection for convolutional automatic speech recognition0
Explaining non-linear Classifier Decisions within Kernel-based Deep Architectures0
Methods for Segmentation and Classification of Digital Microscopy Tissue Images0
Structure Learning of Deep Neural Networks with Q-Learning0
Weak-supervision for Deep Representation Learning under Class Imbalance0
Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image ClassificationCode0
DropBlock: A regularization method for convolutional networksCode0
Piecewise Strong Convexity of Neural Networks0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified