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 9101–9150 of 10420 papers

TitleStatusHype
Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery—0
Adversarial Learning of Label Dependency: A Novel Framework for Multi-class Classification—0
A Smart System for Selection of Optimal Product Images in E-Commerce—0
Fashion and Apparel Classification using Convolutional Neural Networks—0
ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks—0
Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles—0
FLOPs as a Direct Optimization Objective for Learning Sparse Neural Networks—0
Prototypical Clustering Networks for Dermatological Disease Diagnosis—0
Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and BeyondCode0
DSNet: Deep and Shallow Feature Learning for Efficient Visual Tracking—0
SparseFool: a few pixels make a big differenceCode0
Semantic bottleneck for computer vision tasks—0
A Biologically Plausible Learning Rule for Deep Learning in the BrainCode0
FUNN: Flexible Unsupervised Neural Network—0
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification—0
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scaleCode0
Unauthorized AI cannot Recognize Me: Reversible Adversarial Example—0
Introspection for convolutional automatic speech recognition—0
Explaining non-linear Classifier Decisions within Kernel-based Deep Architectures—0
Methods for Segmentation and Classification of Digital Microscopy Tissue Images—0
Structure Learning of Deep Neural Networks with Q-Learning—0
Weak-supervision for Deep Representation Learning under Class Imbalance—0
Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image ClassificationCode0
DropBlock: A regularization method for convolutional networksCode0
Piecewise Strong Convexity of Neural Networks—0
Recurrent Attention Unit—0
Learning to Teach with Dynamic Loss Functions—0
Learning and Interpreting Multi-Multi-Instance Learning Networks—0
Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication—0
Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features—0
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning—0
Sleep-like slow oscillations improve visual classification through synaptic homeostasis and memory association in a thalamo-cortical model—0
On the Confidence of Neural Network Predictions for some NLP Tasks—0
Deep multi-survey classification of variable stars—0
Hierarchical ResNeXt Models for Breast Cancer Histology Image Classification—0
Automated identification of hookahs (waterpipes) on Instagram: an application in feature extraction using Convolutional Neural Network and Support Vector Machine classification—0
To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference—0
KTAN: Knowledge Transfer Adversarial Network—0
Projecting Trouble: Light Based Adversarial Attacks on Deep Learning Classifiers—0
Approximate Fisher Information Matrix to Characterise the Training of Deep Neural NetworksCode0
Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape AnalysisCode0
Compressively Sensed Image Recognition—0
Super Characters: A Conversion from Sentiment Classification to Image Classification—0
Uncertainty in Neural Networks: Approximately Bayesian EnsemblingCode0
Effects of Image Degradations to CNN-based Image Classification—0
Does Haze Removal Help CNN-based Image Classification?—0
Which Has Better Visual Quality: The Clear Blue Sky or a Blurry Animal?Code0
Automatic Configuration of Deep Neural Networks with EGOCode0
Efficient Computation of Quantized Neural Networks by −1, +1 Encoding Decomposition—0
Diagnosing Convolutional Neural Networks using their Spectral Response—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