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 95019525 of 10420 papers

TitleStatusHype
Discriminative and Geometry Aware Unsupervised Domain Adaptation0
Large-Scale 3D Scene Classification With Multi-View Volumetric CNN0
A Deep Learning Interpretable Classifier for Diabetic Retinopathy Disease Grading0
Wolf in Sheep's Clothing - The Downscaling Attack Against Deep Learning Applications0
BT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition0
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted LabelsCode0
A Particle Swarm Optimization-based Flexible Convolutional Auto-Encoder for Image ClassificationCode0
Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video ClassificationCode0
The Effectiveness of Data Augmentation in Image Classification using Deep LearningCode0
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer0
Predicting Yelp Star Reviews Based on Network Structure with Deep LearningCode0
StrassenNets: Deep Learning with a Multiplication BudgetCode0
An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image ClassificationCode0
Gradient Normalization & Depth Based Decay For Deep Learning0
Basic Thresholding Classification0
Defense against Adversarial Attacks Using High-Level Representation Guided DenoiserCode0
In-Place Activated BatchNorm for Memory-Optimized Training of DNNsCode0
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing0
Maximum Classifier Discrepancy for Unsupervised Domain AdaptationCode1
Deep Gradient Compression Reduce the Communication Bandwidth For distributed TraningCode0
OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep LearningCode0
What's in my closet?: Image classification using fuzzy logic0
Successive Embedding and Classification Loss for Aerial Image ClassificationCode0
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed TrainingCode0
Raw Waveform-based Audio Classification Using Sample-level CNN Architectures0
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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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified