Implementing polyp segmentation using the U-Net and CVC-612 dataset.

Official implementation of ColonSegNet: Real-Time Polyp Segmentation (Used in NVIDIA Clara Holoscan App for Polyp Segmentation)

[TMI'22] A Source-free Domain Adaptive Polyp Detection Framework with Style Diversification Flow

[MICCAI 2025 Early Accept] Targeted False Positive Synthesis via Detector-guided Adversarial Diffusion Attacker for Robust Polyp Detection

Polyp Localization In Colonscopy Videos using Single Shot Multibox Detector

A systematic study on the performance of different data augmentation methods for colon polyp detection.

Polyp-Classification-using-CNN

This repository contains the BKM for training YOLOv11n model on Intel Arc A770 GPU and the reference implementation of polyp detection in colonoscopy video with the optimized model using OpenVINO 2025

[MICCAI'22] Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection.

This research will show an innovative method useful in the segmentation of polyps during the screening phases of colonoscopies. To do this we have adopted a new approach which consists in merging the hybrid semantic network (HSNet) architecture model with the Reagion-wise(RW) as a loss function for the backpropagation process.