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mish

Here are 7 public repositories matching this topic...

CoinCheung / pytorch-loss

label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

cuda pytorch ema triplet-loss label-smoothing focal-loss amsoftmax dice-loss mish lovasz-softmax partial-fc

Updated Oct 17, 2024
Python

maudzung / Complex-YOLOv4-Pytorch

The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"

real-time multiprocessing lidar object-detection mosaic lidar-point-cloud 3d-object-detection data-parallel-computing complex-yolo giou mish yolov4 rotated-boxes rotated-boxes-iou

Updated Aug 30, 2024
Python

soumik12345 / Pix2Pix

Image to Image Translation using Conditional GANs (Pix2Pix) implemented using Tensorflow 2.0

tensorflow google-maps keras gan pix2pix image-translation cityscapes conditional-gan tensorflow-pix2pix activation-functions mish

Updated Jan 24, 2020
Jupyter Notebook

bsridatta / Rotated-Object-Detection

Tiny ResNet inspired FPN network (<2M params) for Rotated Object Detection using 5-parameter Modulated Rotation Loss

research pytorch tiny resnet object-detection callbacks lmr fpn multi-head rotated-box mish wandb weights-and-biases rotated-boxes-iou rotated-object modulated-rotation-loss

Updated Jul 8, 2021
Python

soumik12345 / Enet

Pytorch Implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation (https://arxiv.org/abs/1606.02147)

deep-learning pytorch enet semantic-segmentation camvid-dataset real-time-semantic-segmentation mish

Updated Jan 24, 2020
Jupyter Notebook

TmohamedashrafT / Yolov4-implementation

Implementing the training pipeline for YOLOv4 using PyTorch

pytorch object-detection spp mean-average-precision panet mish yolov4 ciou-loss csbdarknet53

Updated Dec 15, 2023
Jupyter Notebook

NamanMakkar / UoE-INFR11031-Advanced-Vision-CW-21-22

This repository contains the code and the report for the coursework of INFR11031 Advanced Vision, a postgraduate course offered at The University of Edinburgh. The task was to train on limited and improve the accuracy of the ResNet-50 classifier on a small subset of the ImageNet dataset containing 50K training images and 50K test images. Achieve…

swish imagenet resnet limited-data adversarial-training autoaugment gelu mixed-precision-training mish randaugment mixup-cutmix cutmix-augmentation

Updated Jul 2, 2022
Jupyter Notebook

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