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 5701–5750 of 10420 papers

TitleStatusHype
An evaluation of pre-trained models for feature extraction in image classification—0
Do Convnets Learn Correspondence?—0
Do Better ImageNet Models Transfer Better?—0
Breast Tumor Classification and Segmentation using Convolutional Neural Networks—0
A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks—0
DMSANet: Dual Multi Scale Attention Network—0
DM-CT: Consistency Training with Data and Model Perturbation—0
Breast Cancer Image Classification Method Based on Deep Transfer Learning—0
DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning—0
DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs (Extended)—0
Diving into Optimization of Topology in Neural Networks—0
Breast Cancer Diagnosis Using Machine Learning Techniques—0
A Neural ODE Interpretation of Transformer Layers—0
A deep primal-dual proximal network for image restoration—0
Diversity Matters When Learning From Ensembles—0
Breast Cancer Detection and Diagnosis: A comparative study of state-of-the-arts deep learning architectures—0
Diversity-Driven Learning: Tackling Spurious Correlations and Data Heterogeneity in Federated Models—0
Diversifying Sample Generation for Accurate Data-Free Quantization—0
Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack—0
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning—0
Diversified Ensembling: An Experiment in Crowdsourced Machine Learning—0
Brain tumor grade classification Using LSTM Neural Networks with Domain Pre-Transforms—0
A Neural Markovian Multiresolution Image Labeling Algorithm—0
Diverse Feature Learning by Self-distillation and Reset—0
Brain Tumor Detection and Classification Using a New Evolutionary Convolutional Neural Network—0
Divergent Search for Few-Shot Image Classification—0
Brain Tumor Classification Using Medial Residual Encoder Layers—0
Brain Storm Optimization Based Swarm Learning for Diabetic Retinopathy Image Classification—0
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions—0
Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning—0
A Network Framework for Noisy Label Aggregation in Social Media—0
A Deep Model for Partial Multi-Label Image Classification with Curriculum Based Disambiguation—0
A Deep Learning Interpretable Classifier for Diabetic Retinopathy Disease Grading—0
A Combinatorial Approach to Neural Emergent Communication—0
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training—0
Distribution-sensitive Information Retention for Accurate Binary Neural Network—0
Distribution Learning Based on Evolutionary Algorithm Assisted Deep Neural Networks for Imbalanced Image Classification—0
Distribution-Aware Adaptive Multi-Bit Quantization—0
Brain Inspired Adaptive Memory Dual-Net for Few-Shot Image Classification—0
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations—0
Robust Multi-instance Learning with Stable Instances—0
BraidNet: procedural generation of neural networks for image classification problems using braid theory—0
A Network Architecture for Point Cloud Classification via Automatic Depth Images Generation—0
Distributional loss for convolutional neural network regression and application to GNSS multi-path estimation—0
Task-Robust Model-Agnostic Meta-Learning—0
Distribution Adaptive INT8 Quantization for Training CNNs—0
Boundary Unlearning: Rapid Forgetting of Deep Networks via Shifting the Decision Boundary—0
An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images—0
Distributed Transfer Learning with 4th Gen Intel Xeon Processors—0
Distributed Training of Deep Neural Networks with Theoretical Analysis: Under SSP Setting—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