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 8601–8650 of 10420 papers

TitleStatusHype
Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks—0
Adversarial Examples for Edge Detection: They Exist, and They Transfer—0
GANchors: Realistic Image Perturbation Distributions for Anchors Using Generative ModelsCode0
Detecting Anomalies in Image Classification by Means of Semantic RelationshipsCode0
Compact Feature Learning for Multi-Domain Image Classification—0
Not Using the Car to See the Sidewalk -- Quantifying and Controlling the Effects of Context in Classification and Segmentation—0
Embedding Complementary Deep Networks for Image Classification—0
A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks—0
Adapting Object Detectors via Selective Cross-Domain AlignmentCode0
ImageTTR: Grounding Type Theory with Records in Image Classification for Visual Question Answering—0
Exploration of Noise Strategies in Semi-supervised Named Entity Classification—0
Perceptual Evaluation of Adversarial Attacks for CNN-based Image ClassificationCode0
Versatile Multiple Choice Learning and Its Application to Vision Computing—0
Weakly Supervised Image Classification Through Noise Regularization—0
Spot and Learn: A Maximum-Entropy Patch Sampler for Few-Shot Image Classification—0
Structured Knowledge Distillation for Semantic SegmentationCode0
Visual Attention Consistency Under Image Transforms for Multi-Label Image ClassificationCode0
Transferable AutoML by Model Sharing Over Grouped Datasets—0
Fast Solar Image Classification Using Deep Learning and its Importance for Automation in Solar PhysicsCode0
Multi-Precision Quantized Neural Networks via Encoding Decomposition of -1 and +1—0
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial RobustnessCode0
Characterizing Bias in Classifiers using Generative ModelsCode0
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification—0
Deep multi-class learning from label proportions—0
Toward Runtime-Throttleable Neural Networks—0
Training Data Subset Search with Ensemble Active Learning—0
A Study of BFLOAT16 for Deep Learning Training—0
An Inertial Newton Algorithm for Deep LearningCode0
Replica-exchange Nosé-Hoover dynamics for Bayesian learning on large datasets—0
Empirically Measuring Concentration: Fundamental Limits on Intrinsic RobustnessCode0
RecNets: Channel-wise Recurrent Convolutional Neural Networks—0
Why gradient clipping accelerates training: A theoretical justification for adaptivityCode0
A Compact Representation of Histopathology Images using Digital Stain Separation & Frequency-Based Encoded Local Projections—0
Image classification using quantum inference on the D-Wave 2X—0
Differential Privacy Has Disparate Impact on Model AccuracyCode0
Network DeconvolutionCode0
Inference with Hybrid Bio-hardware Neural Networks—0
Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion—0
Bayesian Nonparametric Federated Learning of Neural NetworksCode0
CompactNet: Platform-Aware Automatic Optimization for Convolutional Neural NetworksCode0
Efficient Object Embedding for Spliced Image Retrieval—0
Texture CNN for Thermoelectric Metal Pipe Image Classification—0
Texture CNN for Histopathological Image Classification—0
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural NetworksCode0
A Rate-Distortion Framework for Explaining Neural Network DecisionsCode0
Improved Training Speed, Accuracy, and Data Utilization Through Loss Function OptimizationCode0
Defining Quantum Neural Networks via Quantum Time Evolution—0
Capsule Routing via Variational BayesCode0
Robust Classification using Robust Feature Augmentation—0
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified