Alternatives and similar repositories for Endoscopic-colorectal-polyp-detection-based-on-improved-YOLOv8

Users that are interested in Endoscopic-colorectal-polyp-detection-based-on-improved-YOLOv8 are comparing it to the libraries listed below

• mkang315 / ASF-YOLO
  [IMAVIS] Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
  ☆101Updated this week
• arojsubedi / WIoU
  WIoU implementation for the YOLOv8
  ☆17Updated last year
• mkang315 / RCS-YOLO
  [MICCAI'23] Official implementation of "RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection".
  ☆94Updated 2 months ago
• mkang315 / BGF-YOLO
  [MICCAI'24] Official implementation of "BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection".
  ☆137Updated 2 months ago
• RuiyangJu / Fracture_Detection_Improved_YOLOv8
  ICONIP 2024 (IEEE Access 2025)
  ☆122Updated last month
• scuzyq / improved-v8
  Improved-YOLOv8
  ☆24Updated 11 months ago
• mcw1217 / MultiModal-YOLO_RGB_Depth_Thermal
  This project uses three types of images as inputs RGB, Depth, and thermal images to perform object detection with YOLOv8.
  ☆24Updated last year
• Kacper-Marciniak / YOLOv8-Framework
  Framework for object detection and instance segmentation models from the YOLOv8 family with SAM support
  ☆10Updated 6 months ago
• arojsubedi / Improved-YOLOv8s
  The baseline YOLOv8s model has been improved with the integration of Global Attention Mechanism (GAM), Modified Neck, and Wise Intersecti…
  ☆34Updated last month
• JustlfC03 / MFDS-DETR
  [CIBM] Accurate Leukocyte Detection Based on Deformable-DETR and Multi-Level Feature Fusion for Aiding Diagnosis of Blood Diseases
  ☆72Updated last year
• mkang315 / CST-YOLO
  [ICIP'24 Lecture Presentation] Official implementation of "CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and…
  ☆72Updated 2 weeks ago
• chengshuxiao / YOLOv5-ODConvNeXt
  YOLOv5-ODConvNeXt is an improved version of YOLOv5 for ship detection on drone-captured images.
  ☆58Updated 2 years ago
• SwjtuMa / FER-YOLO-Mamba
  ☆96Updated last year
• gyyang23 / AFPN
  ☆135Updated last year
• dengbuqi / GAM_Pytorch
  Pytorch Implement of Global Attention Mechanism from "Global Attention Mechanism: Retain Information to Enhance Channel-Spatial Interacti…
  ☆12Updated 3 years ago
• zhengshuchen / HCFNet
  ☆118Updated 7 months ago
• mbl1234 / YOLOv8_PYQT5_GUI
  基于YOLOv8和PYQT5的检测界面
  ☆45Updated last year
• CV-ZhangXin / LDConv
  ☆120Updated 4 months ago
• Marfbin / NEU-DET-with-yolov8
  The dataset I am using is NEU-DET, which uses yolov8 and its improved models (including Coordinate Attention and Swin Transformer) for de…
  ☆98Updated last year
• HZAI-ZJNU / SCSA
  The official pytorch implementation of "SCSA: Exploring the Synergistic Effects Between Spatial and Channel Attention".
  ☆104Updated 8 months ago
• Instinct323 / Wise-IoU
  Wise-IoU: Bounding Box Regression Loss with Dynamic Focusing Mechanism
  ☆90Updated last year
• rorubyy / thermal_rgb_fusion_yolov8
  ☆18Updated 2 years ago
• LuYang-2023 / Insulator-Defect-Detection-YOLO
  ☆22Updated 5 months ago
• a875560134 / YOLOv8-Improved
  ☆14Updated last year
• haichao67 / GD-YOLOv8
  Lightweight Rail Surface Defect Detection Algorithm Based on an Improved YOLOv8
  ☆36Updated 8 months ago
• danfenghong / IEEE_TIP_UIU-Net
  Xin Wu, Danfeng Hong, Jocelyn Chanussot. UIU-Net: U-Net in U-Net for Infrared Small Object Detection, IEEE Trans. Image. Process., 2022, …
  ☆166Updated 2 years ago
• yangdi-cv / TP-YOLO
  [ICIP2023] TP-YOLO: A Lightweight Attention-Based Architecture for Tiny Pest Detection
  ☆16Updated last year
• QY1994-0919 / CFPNet
  Centralized Feature Pyramid for Object Detection
  ☆251Updated 2 years ago
• LZY-233 / yolov8_Imporved-Defect_detection
  Steel defect detection system based on improved YOLOv8 algorithm(基于改进YOLOv8算法的钢材瑕疵辅助检测系统)
  ☆32Updated last year
• duong-db / U-Lite
  A lightweight CNN-based model for medical image segmentation.
  ☆102Updated last year