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

Showing 98519875 of 10420 papers

TitleStatusHype
Regularizing Neural Networks by Penalizing Confident Output DistributionsCode0
Loss-Sensitive Generative Adversarial Networks on Lipschitz DensitiesCode0
A New Convolutional Network-in-Network Structure and Its Applications in Skin Detection, Semantic Segmentation, and Artifact Reduction0
Convolutional Oriented Boundaries: From Image Segmentation to High-Level TasksCode0
Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading0
Cost-Effective Active Learning for Deep Image ClassificationCode0
An OpenCL(TM) Deep Learning Accelerator on Arria 100
Deep Learning for Logo Recognition0
Classification Accuracy Improvement for Neuromorphic Computing Systems with One-level Precision Synapses0
Oriented Response NetworksCode0
Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation0
Weakly Supervised Semantic Segmentation using Web-Crawled Videos0
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution0
Rotation equivariant vector field networksCode0
MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification0
An Automated CNN Recommendation System for Image Classification Tasks0
Steerable CNNsCode1
Wide-Slice Residual Networks for Food RecognitionCode0
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomicsCode0
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network0
Coupling Adaptive Batch Sizes with Learning RatesCode0
The More You Know: Using Knowledge Graphs for Image Classification0
Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel ClassificationCode0
Co-localization with Category-Consistent Features and Geodesic Distance Propagation0
Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified