SOTAVerified

Quantization

Quantization is a promising technique to reduce the computation cost of neural network training, which can replace high-cost floating-point numbers (e.g., float32) with low-cost fixed-point numbers (e.g., int8/int16).

Source: Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3726–3750 of 4925 papers

TitleStatusHype
Algorithm and VLSI Design for 1-bit Data Detection in Massive MIMO-OFDMCode0
Deep data compression for approximate ultrasonic image formation—0
Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors—0
A new heuristic algorithm for fast k-segmentation—0
Transform Quantization for CNN (Convolutional Neural Network) Compression—0
Object Detection-Based Variable Quantization Processing—0
Heatmap Regression via Randomized RoundingCode1
Scaling Up Deep Neural Network Optimization for Edge Inference—0
An Integrated Approach to Produce Robust Models with High EfficiencyCode0
Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond—0
An adaptive random experiment design method for engineering experiment—0
GAN Slimming: All-in-One GAN Compression by A Unified Optimization FrameworkCode1
Stochastic Markov Gradient Descent and Training Low-Bit Neural Networks—0
Convergence of Federated Learning over a Noisy Downlink—0
Stochastic Hybrid Combining Design for Quantized Massive MIMO Systems—0
Lossy Image Compression with Normalizing Flows—0
One Weight Bitwidth to Rule Them All—0
Training of mixed-signal optical convolutional neural network with reduced quantization level—0
Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks—0
Channel-wise Hessian Aware trace-Weighted Quantization of Neural Networks—0
False Detection (Positives and Negatives) in Object Detection—0
ECG beats classification via online sparse dictionary and time pyramid matchingCode0
Weight Equalizing Shift Scaler-Coupled Post-training Quantization—0
Leveraging Automated Mixed-Low-Precision Quantization for tiny edge microcontrollers—0
Compression of Deep Learning Models for Text: A Survey—0
Show:102550
← PrevPage 150 of 197Next →
All datasetsImageNetCIFAR-10Wiki-40BAgeDB-30CFP-FPCOCO (Common Objects in Context)IJB-BIJB-CKnowledge-based:LFW

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FQ-ViT (ViT-L)Top-1 Accuracy (%)85.03—Unverified
2FQ-ViT (ViT-B)Top-1 Accuracy (%)83.31—Unverified
3FQ-ViT (Swin-B)Top-1 Accuracy (%)82.97—Unverified
4FQ-ViT (Swin-S)Top-1 Accuracy (%)82.71—Unverified
5FQ-ViT (DeiT-B)Top-1 Accuracy (%)81.2—Unverified
6FQ-ViT (Swin-T)Top-1 Accuracy (%)80.51—Unverified
7FQ-ViT (DeiT-S)Top-1 Accuracy (%)79.17—Unverified
8Xception W8A8Top-1 Accuracy (%)78.97—Unverified
9ADLIK-MO-ResNet50-W4A4Top-1 Accuracy (%)77.88—Unverified
10ADLIK-MO-ResNet50-W3A4Top-1 Accuracy (%)77.34—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_3MAP160,327.04—Unverified
2DTQMAP0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1OutEffHop-Bert_basePerplexity6.3—Unverified
2OutEffHop-Bert_basePerplexity6.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy98.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy92.92—Unverified
#ModelMetricClaimedVerifiedStatus
1SSD ResNet50 V1 FPN 640x640MAP34.3—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-495.13—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-496.38—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_5All84,809,664—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy99.8—Unverified