Skip to content
Universidad del Mar SIBUMAR Descubridor Institucional UMAR
  • Inicio
  • Búsqueda avanzada
  • Explorar
  • Login
    • English
    • Deutsch
    • Español
    • Français
    • Italiano
Advanced
  • Quantizing YOLOv7: A Comprehensive Study
Cover Image

Quantizing YOLOv7: A Comprehensive Study

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Baghbanbashi, Mohammadamin, Raji, Mohsen, Ghavami, Behnam
Format: Preprint
Published: 2024
Subjects:
Computer Vision and Pattern Recognition
Hardware Architecture
Machine Learning
I.2.10; I.4.0; I.5.1; E.4
Online Access:
Acceder al recurso
Tags: Add Tag
No Tags, Be the first to tag this record!
  • Cite this
  • Text this
  • Email this
  • Print
  • Export Record
    • Export to RefWorks
    • Export to EndNoteWeb
    • Export to EndNote
  • Save to List
  • Permanent link
  • Holdings
  • Description
  • Comments
  • Similar Items
  • Staff View

Internet

https://arxiv.org/abs/2407.04943

Similar Items

  • Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Survey
    by: Rajapaksha, Uchitha, et al.
    Published: (2024)
  • FAME: Feature Activation Map Explanation on Image Classification and Face Recognition
    by: Zhang, Xinyi, et al.
    Published: (2026)
  • GeoPos: A Minimal Positional Encoding for Enhanced Fine-Grained Details in Image Synthesis Using Convolutional Neural Networks
    by: Hosseini, Mehran, et al.
    Published: (2024)
  • WaveMix: A Resource-efficient Neural Network for Image Analysis
    by: Jeevan, Pranav, et al.
    Published: (2022)
  • Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision
    by: Jeevan, Pranav, et al.
    Published: (2024)
Universidad del Mar
Universidad del MarSistema Bibliotecario de la Universidad del MarDescubridor Institucional UMARImplementación y desarrollo: Mtro. Carlos Alonso Albores Pérez
InicioBúsqueda avanzadaExplorar
Visitas al Descubridor: 33,245© 2026 Universidad del Mar