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 7676–7700 of 10420 papers

TitleStatusHype
Radio Signal Classification by Adversarially Robust Quantum Machine Learning—0
Putting GPT-4o to the Sword: A Comprehensive Evaluation of Language, Vision, Speech, and Multimodal Proficiency—0
Flip-Rotate-Pooling Convolution and Split Dropout on Convolution Neural Networks for Image Classification—0
A Sparse Coding Interpretation of Neural Networks and Theoretical Implications—0
Radial Basis Feature Transformation to Arm CNNs Against Adversarial Attacks—0
RadTex: Learning Efficient Radiograph Representations from Text Reports—0
ASP:A Fast Adversarial Attack Example Generation Framework based on Adversarial Saliency Prediction—0
RA-CLIP: Retrieval Augmented Contrastive Language-Image Pre-Training—0
Flatten: Video Action Recognition is an Image Classification task—0
Pyramidal RoR for Image Classification—0
PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining—0
Connecting metrics for shape-texture knowledge in computer vision—0
A Free-Energy Principle for Representation Learning—0
RAID: Randomized Adversarial-Input Detection for Neural Networks—0
Random Forests and VGG-NET: An Algorithm for the ISIC 2017 Skin Lesion Classification Challenge—0
Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscape—0
Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks—0
Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models—0
Conjugate-gradient-based Adam for stochastic optimization and its application to deep learning—0
CongNaMul: A Dataset for Advanced Image Processing of Soybean Sprouts—0
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning—0
Image Classification Method using Dynamic Quantum Inspired Genetic Algorithm—0
A Sneak Attack on Segmentation of Medical Images Using Deep Neural Network Classifiers—0
Query-Efficient Decision-based Black-Box Patch Attack—0
A Smart System for Selection of Optimal Product Images in E-Commerce—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
10RevCol-HTop 1 Accuracy90—Unverified