SPECHT is a Julia implementation of a contrastive weakly supervised object detection and identification method for fluorescence microscopy.
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Updated
Sep 25, 2024 - Julia
SPECHT is a Julia implementation of a contrastive weakly supervised object detection and identification method for fluorescence microscopy.
Weakly supervised street text detection, localisation and segmentation in Pytorch
Generative Adversarial Learning Towards Fast Weakly Supervised Detection
Weakly Supervised Learning for Findings Detection in Medical Image
Implementation of WSDDN in PyTorch
CAM using GSAP
Pytorch Implementation for "Deep Patch Learning for Weakly Supervised Object Classification and Discovery"
First position in Gran Canary Datathon 2021
W-TALC: Weakly-supervised Temporal Activity Localization and Classification
Codes for: D-MIL: Discrepant multiple instance learning for weakly supervised object detection
Enabling Deep Residual Networks for Weakly Supervised Object Detection
UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object Detection
Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation
Category-Aware Spatial Constraint for Weakly Supervised Detection
This repository contains the code used for the paper "Towards automated brain aneurysm detection in TOF-MRA: open data, weak labels, and anatomical knowledge "
ECCV2022, Point-to-Box Network for Accurate Object Detection via Single Point Supervision
Weakly-supervised Action Localization
Enabling Deep Residual Networks for Weakly Supervised Object Detection
Implementation of Weakly Supervised Deep Detection Networks using the latest version of PyTorch
A paper list of state-of-the-art weakly supervised object detection or localization.
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