Classification
Classification is the task of categorizing a set of data into predefined classes or groups. The aim of classification is to train a model to correctly predict the class or group of new, unseen data. The model is trained on a labeled dataset where each instance is assigned a class label. The learning algorithm then builds a mapping between the features of the data and the class labels. This mapping is then used to predict the class label of new, unseen data points. The quality of the prediction is usually evaluated using metrics such as accuracy, precision, and recall.
Papers
Showing 51–75 of 12815 papers
All datasetsInDLMHISTN-ImageNetSPOT-10Full-body Parkinson’s disease datasetAutoimmune DatasetN-CARSN-ImageNet (mini)ImageNet C-OOD (class-out-of-distribution)CWRU Bearing DatasetBurr classification imagesForgeryNet
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ConvNext | Average Recall | 93.47 | — | Unverified |
| 2 | VGG16 | Average Recall | 92.86 | — | Unverified |
| 3 | DenseNet201 | Average Recall | 90.99 | — | Unverified |
| 4 | Inception ResNet V2 | Average Recall | 90.27 | — | Unverified |
| 5 | Xception | Average Recall | 89.81 | — | Unverified |
| 6 | NASNetLarge | Average Recall | 89.52 | — | Unverified |
| 7 | Darknet53 | Average Recall | 88.53 | — | Unverified |
| 8 | ResNetV2_50 | Average Recall | 88.08 | — | Unverified |
| 9 | MobileNetV3 | Average Recall | 84.28 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MoCo-v2 (ResNet-50) | Accuracy | 88.03 | — | Unverified |
| 2 | MoCo-v2 (ResNet-50) | Accuracy | 85.88 | — | Unverified |
| 3 | Barlow Twins (ResNet-50) | Accuracy | 84.03 | — | Unverified |
| 4 | SwAV (ResNet-50) | Accuracy | 83.21 | — | Unverified |
| 5 | Supervised (ViT-S/16) | Accuracy | 81.68 | — | Unverified |
| 6 | Barlow Rwins (ResNet-50) | Accuracy | 81.27 | — | Unverified |
| 7 | DINO (ViT-S/16) | Accuracy | 79.43 | — | Unverified |
| 8 | Supervised (ResNet-50) | Accuracy | 78.92 | — | Unverified |
| 9 | SwAV (ResNet-50) | Accuracy | 77.99 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Event Spike Tensor | Accuracy (%) | 48.93 | — | Unverified |
| 2 | DiST | Accuracy (%) | 48.43 | — | Unverified |
| 3 | Sorted Time Surface | Accuracy (%) | 47.9 | — | Unverified |
| 4 | Event Histogram | Accuracy (%) | 47.73 | — | Unverified |
| 5 | HATS | Accuracy (%) | 47.14 | — | Unverified |
| 6 | Binary Event Image | Accuracy (%) | 46.36 | — | Unverified |
| 7 | Timestamp Image | Accuracy (%) | 45.86 | — | Unverified |
| 8 | Event Image | Accuracy (%) | 45.77 | — | Unverified |
| 9 | Time Surface | Accuracy (%) | 44.32 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | DenseNet121 Distiller | Accuracy | 81.84 | — | Unverified |
| 2 | ResNet101V2 Distiller | Accuracy | 80.29 | — | Unverified |
| 3 | ResNet50V2 Distiller | Accuracy | 79.03 | — | Unverified |
| 4 | MobileNet Distiller | Accuracy | 78.26 | — | Unverified |
| 5 | MobileNetV3Small Distiller | Accuracy | 78.04 | — | Unverified |
| 6 | MobileNetV3Large Distiller | Accuracy | 77.88 | — | Unverified |
| 7 | NASNetMobile Distiller | Accuracy | 77.75 | — | Unverified |
| 8 | MobileNetV2 Distiller | Accuracy | 77.53 | — | Unverified |
| 9 | ResNet50 Distiller | Accuracy | 77.45 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | PoseFormerV2 | F1-score (weighted) | 0.59 | — | Unverified |
| 2 | PD STGCN | F1-score (weighted) | 0.48 | — | Unverified |
| 3 | MotionBERT | F1-score (weighted) | 0.47 | — | Unverified |
| 4 | Pose Transformers (POTR) | F1-score (weighted) | 0.46 | — | Unverified |
| 5 | MotionBERT-LITE | F1-score (weighted) | 0.43 | — | Unverified |
| 6 | MotionAGFormer | F1-score (weighted) | 0.42 | — | Unverified |
| 7 | Mixste | F1-score (weighted) | 0.41 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Swin Transformer Base (Patch 4 Window 12) | F1 score | 0.89 | — | Unverified |
| 2 | CASS | F1 score | 0.89 | — | Unverified |
| 3 | CASS | F1 score | 0.87 | — | Unverified |
| 4 | DINO | F1 score | 0.86 | — | Unverified |
| 5 | DINO | F1 score | 0.84 | — | Unverified |
| 6 | VANBUREN et all | F1 score | 0.63 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MEM | Accuracy (%) | 98.55 | — | Unverified |
| 2 | GET | Accuracy (%) | 96.7 | — | Unverified |
| 3 | ResNet34 + EST | Accuracy (%) | 92.5 | — | Unverified |
| 4 | Spiking VGG-11 | Accuracy (%) | 92.4 | — | Unverified |
| 5 | Spiking MobileNet-64 | Accuracy (%) | 91.7 | — | Unverified |
| 6 | Spiking DenseNet121-24 | Accuracy (%) | 90.4 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Event Imge | Accuracy (%) | 61.42 | — | Unverified |
| 2 | Event Histogram | Accuracy (%) | 61.02 | — | Unverified |
| 3 | Timestamp Image | Accuracy (%) | 60.46 | — | Unverified |
| 4 | DiST | Accuracy (%) | 59.74 | — | Unverified |
| 5 | Sorted Time Surface | Accuracy (%) | 58.38 | — | Unverified |
| 6 | Binary Event Image | Accuracy (%) | 53.52 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ViT-L/32-384 with Max-logit | Detection AUROC (severity 0) | 1 | — | Unverified |
| 2 | ViT-L/32-384 with ODIN | Detection AUROC (severity 0) | 1 | — | Unverified |
| 3 | ViT-L/32-384 with Entropy | Detection AUROC (severity 0) | 0.99 | — | Unverified |
| 4 | ViT-L/32-384 with MC Dropout | Detection AUROC (severity 0) | 0.99 | — | Unverified |
| 5 | ViT-L/32-384 with Softmax | Detection AUROC (severity 0) | 0.99 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MixMamba-Fewshot | 10 fold Cross validation | 99.93 | — | Unverified |
| 2 | Few-shot Transformer Covariance | 10 fold Cross validation | 99.86 | — | Unverified |
| 3 | MCNN-LSTM | 10 fold Cross validation | 98.46 | — | Unverified |
| 4 | CNN | 10 fold Cross validation | 7 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | 70_divisions | precision | 93.2 | — | Unverified |
| 2 | 60_divisions | precision | 93.2 | — | Unverified |
| 3 | 80_divisions | precision | 93.2 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MINTIME-XC | AUC | 94.25 | — | Unverified |
| 2 | SlowFast R-50 | AUC | 90.86 | — | Unverified |
| 3 | MINTIME-EF | AUC | 90.45 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | DenseNet121 | Robustness Score | 0.91 | — | Unverified |
| 2 | ResNet 50 | Robustness Score | 0.9 | — | Unverified |
| 3 | VGG-16 | Robustness Score | 0.88 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | BIOSCAN_1M_order_classifier | Macro F1 | 92.65 | — | Unverified |
| 2 | BIOSCAN_1M_family_classifier | Macro F1 | 91.45 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | GPT-4 | 1 shot Micro-F1 | 96.86 | — | Unverified |
| 2 | BiLSTM-CRF | 1 shot Micro-F1 | 82.2 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SVM | F1-score (Weighted) | 86.19 | — | Unverified |
| 2 | RoBERTa | F1-score (Weighted) | 78.13 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | GLNet | 1:1 Accuracy | 95.07 | — | Unverified |
| 2 | CPM | 1:1 Accuracy | 50 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ELM Neuron | Accuracy (%) | 82 | — | Unverified |
| 2 | LSTM | Accuracy (%) | 10 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MambaNet | AUROC | 0.91 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | RandomForestClassifier | Accuracy | 82 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | CNN + Attention + LSTM + CNN | Accuracy (%) | 86.91 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | WeaSEL | 1:1 Accuracy | 86 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | DINO | F1 score | 0.99 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | AAPSO-Deep Feature Selection | Accuracy | 98.41 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | CNN | Validation Accuracy | 93.55 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ResNet8×4 | Accuracy | 77.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ViT-L/16 (Background) | Accuracy on Brightness Corrupted Images | 99.03 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Random Forest | AUC | 0.97 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | lstm | Accuracy | 0.72 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MSTP | Accuracy | 95.11 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | RECALL | Overall accuracy after last sequence | 57.83 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | RECALL | Overall accuracy after last sequence | 4,065 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | RRWNet | Accuracy | 0.98 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | TD-CNN- Attention | F1 score | 99.71 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | CLIP-RN50x64 | 1-of-100 Accuracy | 61 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SVM | F1 (%) | 97.72 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | RRWNet | Accuracy | 0.95 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | HSQformer | AUC | 83.83 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | WaferSegClassNet | Accuracy | 0.98 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | C-Tran, preprocessing, augmentation | ML F1 | 0.57 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | μ RadNet | 1:1 Accuracy | 99.22 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Resnet 50 | Accuracy (% ) | 92.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | RRWNet | Accuracy | 0.97 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | pFedBreD_ns_mg | Accuracy | 73.81 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SGD_ss | F1 (Seqeval) | 2,020 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | LangGas | Frame Level Accuracy | 0.89 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | 1DCNN-ResNet | macro f1 score (A(100), B(100), C(100) Avg.) | 0.99 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | BRIDGE | Accuracy | 25.6 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MSI-H Transformer | AUPRC | 0.58 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | BRIDGE | Accuracy | 42.2 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | BRIDGE | Accuracy | 36.2 | — | Unverified |