An example of using OpenCV dnn module with YOLOv5. (ObjectDetection, Segmentation, Classification)
Обновлено 2024-11-11 20:00:01 +03:00
Perception toolkit for sim2real training and validation in Unity
machine-learning
computer-vision
deep-learning
detection
domain-randomization
object-detection
perception
pose-estimation
segmentation
synthetic-dataset-generation
Обновлено 2024-11-08 22:38:42 +03:00
An official implementation for " UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation"
video
localization
segmentation
caption-task
coin
joint
msrvtt
multimodal-sentiment-analysis
multimodality
pretrain
pretraining
retrieval-task
video-language
video-text
video-text-retrieval
youcookii
alignment
caption
Обновлено 2024-07-25 14:07:31 +03:00
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
object-detection
image-classification
semantic-segmentation
imagenet
swin-transformer
ade20k
mask-rcnn
mscoco
Обновлено 2024-07-15 18:00:32 +03:00
Medical Imaging Deep Learning library to train and deploy 3D segmentation models on Azure Machine Learning
Обновлено 2024-03-21 12:43:17 +03:00
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021)
deep-learning
computer-vision
neural-network
semantic-segmentation
semi-supervised-learning
domain-adaptation
pseudo-label
Обновлено 2023-07-07 00:28:52 +03:00
a transductive approach for video object segmentation
Обновлено 2023-06-27 15:56:56 +03:00
Generates varieties of images of randomized but semantically correct technical diagrams like flow charts and state diagrams. These images can be used to train NNs that perform image segmentation tasks.
Обновлено 2022-12-08 12:25:52 +03:00
Whole Brain Segmentation with Full Volume Neural Network, CMIG
Обновлено 2021-11-03 09:51:33 +03:00
Trend Calculator repository provides an abstracted way to calculate the trending data from the input data. It takes into consideration the window period, input data and the segmentation
Обновлено 2021-08-22 11:12:23 +03:00
Land cover mapping of the Orinoquía region in Colombia, in collaboration with Wildlife Conservation Society Colombia. An #AIforEarth project
Обновлено 2021-03-13 01:26:16 +03:00
Distributed training of Image segmentation on Azure Machine Learning
Обновлено 2021-02-17 22:47:57 +03:00
Deep Learning for Seismic Imaging and Interpretation
microsoft
deep-learning
computer-vision
neural-networks
segmentation
seismic-processing
seismic
seismic-data
seismic-imaging
seismic-inversion
Обновлено 2020-09-19 01:18:20 +03:00
Unsupervised Word Segmentation for Neural Machine Translation and Text Generation
Обновлено 2020-02-21 19:39:42 +03:00
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
microsoft
azure-storage
image-classification
neural-networks
cntk
microsoft-azure
land-cover
land-use
geospatial-data
image-segmentation
microsoft-machine-learning
azure-batchai
cntk-model
geospatial-analysis
Обновлено 2019-07-25 06:53:28 +03:00