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 10101–10150 of 10420 papers

TitleStatusHype
Data-dependent Initializations of Convolutional Neural NetworksCode0
Top-k Multiclass SVMCode0
Semantic Diversity versus Visual Diversity in Visual Dictionaries—0
Training CNNs with Low-Rank Filters for Efficient Image Classification—0
How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?—0
Convolutional Clustering for Unsupervised Learning—0
All you need is a good initCode1
Geodesics of learned representations—0
Compact Bilinear PoolingCode0
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial NetworksCode0
Learning to Generate Images with Perceptual Similarity Metrics—0
Competitive Multi-scale Convolution—0
Sparse learning of maximum likelihood model for optimization of complex loss function—0
Staleness-aware Async-SGD for Distributed Deep LearningCode0
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning—0
Learning Structured Inference Neural Networks with Label Relations—0
DeepFool: a simple and accurate method to fool deep neural networksCode0
Learning Fine-grained Features via a CNN Tree for Large-scale Classification—0
Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning—0
Universum Prescription: Regularization using Unlabeled Data—0
Tiny Descriptors for Image Retrieval with Unsupervised Triplet Hashing—0
The Radon cumulative distribution transform and its application to image classification—0
Batch-normalized Maxout Network in NetworkCode0
Pooling the Convolutional Layers in Deep ConvNets for Action Recognition—0
Image classification based on support vector machine and the fusion of complementary features—0
FireCaffe: near-linear acceleration of deep neural network training on compute clusters—0
Spiking Deep Networks with LIF NeuronsCode0
Aggregating Deep Convolutional Features for Image RetrievalCode0
How Important is Weight Symmetry in Backpropagation?Code1
Layer-Specific Adaptive Learning Rates for Deep Networks—0
Deep convolutional neural networks for pedestrian detectionCode0
DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer—0
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks—0
Relaxed Multiple-Instance SVM with Application to Object Discovery—0
Cross-convolutional-layer Pooling for Image Recognition—0
Human Action Recognition using Factorized Spatio-Temporal Convolutional Networks—0
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and TreeCode0
Mapping Generative Models onto a Network of Digital Spiking Neurons—0
Learning Wake-Sleep Recurrent Attention Models—0
Tensorizing Neural NetworksCode0
Evaluating the visualization of what a Deep Neural Network has learnedCode1
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data—0
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning:A Systematic StudyCode0
Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks—0
DeepSat - A Learning framework for Satellite ImageryCode0
Deep Attributes from Context-Aware Regional Neural Codes—0
Image Classification with Rejection using Contextual Information—0
Computational Integration of Human Vision and Natural Language through Bitext Alignment—0
Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification—0
Fisher Vectors Meet Neural Networks: A Hybrid Classification Architecture—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