PyTorch implementation of RetinaNet with the goal to reproduce results in the "focal loss for dense object detection" paper.
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Updated
Mar 19, 2018 - Python
PyTorch implementation of RetinaNet with the goal to reproduce results in the "focal loss for dense object detection" paper.
PyTorch implementation of RetinaNet
Multi-label text classification in Keras
Deep Face Recognition in PyTorch
Multi-class classification with focal loss for imbalanced datasets
Voice Activity Detection (VAD) using deep learning.
An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems
A sample code for Lightweight Face Recognition competition ICCV2019
Implementation of RetinaNet (focal loss) by TensorFlow (object detection)
Focal CTC for End-To-End OMR task with Class Imbalance, SangCTC (Part I)
A Fully Convolutional Network for car sergmentation
Official implementation of Spatial Feedback Learning to Improve Semantic Segmentation in Hot Weather.
Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection, NeurIPS2020
📦Simple Tool Box with Pytorch
中国法研杯CAIL2019要素抽取任务第三名方案分享
VarifocalNet: An IoU-aware Dense Object Detector
Natural Language Processing: A multi-headed model capable of detecting different types of online discussion toxicity like threats, obscenity, insults, and identity-based hate using Keras RNN LSTM and focal loss to address a hyper-imbalanced dataset.
Feed Forward Neural network: Implemented for bond fluctuation model utilities.
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