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 7601–7650 of 10420 papers

TitleStatusHype
Initialization Noise in Image Gradients and Saliency Maps—0
Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey—0
In-Hindsight Quantization Range Estimation for Quantized Training—0
Informed Non-convex Robust Principal Component Analysis with Features—0
Deep Learning Algorithms for Early Diagnosis of Acute Lymphoblastic Leukemia—0
Informative Robust Causal Representation for Generalizable Deep Learning—0
Informative Class Activation Maps—0
ProtoDiv: Prototype-guided Division of Consistent Pseudo-bags for Whole-slide Image Classification—0
Information-theoretical label embeddings for large-scale image classification—0
Deep Kernel Learning via Random Fourier Features—0
BA^2M: A Batch Aware Attention Module for Image Classification—0
A Method for Restoring the Training Set Distribution in an Image Classifier—0
PrototypeFormer: Learning to Explore Prototype Relationships for Few-shot Image Classification—0
Information Gain Sampling for Active Learning in Medical Image Classification—0
Information contraction in noisy binary neural networks and its implications—0
Prototypical Clustering Networks for Dermatological Disease Diagnosis—0
Joint Device-Edge Inference over Wireless Links with Pruning—0
Pro-tuning: Unified Prompt Tuning for Vision Tasks—0
Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates—0
A Zero-shot Learning Method Based on Large Language Models for Multi-modal Knowledge Graph Embedding—0
Provable Robustness for Streaming Models with a Sliding Window—0
Trade-offs between membership privacy & adversarially robust learning—0
InfoDisent: Explainability of Image Classification Models by Information Disentanglement—0
Deep Integrated Pipeline of Segmentation Guided Classification of Breast Cancer from Ultrasound Images—0
A Melting Pot of Evolution and Learning—0
Provably Improving Generalization of Few-Shot Models with Synthetic Data—0
Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention—0
Inference with Hybrid Bio-hardware Neural Networks—0
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning—0
Inference Time Evidences of Adversarial Attacks for Forensic on Transformers—0
Deep Image Retrieval is not Robust to Label Noise—0
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices—0
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting—0
Inductive Transfer for Neural Architecture Optimization—0
Inducing Functions through Reinforcement Learning without Task Specification—0
Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks—0
Deep Image Destruction: Vulnerability of Deep Image-to-Image Models against Adversarial Attacks—0
Pruning Deep Convolutional Neural Network Using Conditional Mutual Information—0
AME: Attention and Memory Enhancement in Hyper-Parameter Optimization—0
Adaptive Early Exiting for Collaborative Inference over Noisy Wireless Channels—0
Accurate and Resource-Efficient Lipreading with Efficientnetv2 and Transformers—0
MCU: Improving Machine Unlearning through Mode Connectivity—0
Indoor image representation by high-level semantic features—0
In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification—0
Deep Hierarchical Machine: a Flexible Divide-and-Conquer Architecture—0
Deep Hashing: A Joint Approach for Image Signature Learning—0
In-depth Question classification using Convolutional Neural Networks—0
A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning—0
Incremental Open-set Domain Adaptation—0
Incremental Online Learning Algorithms Comparison for Gesture and Visual Smart Sensors—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