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multiModalityFusionForClassification

多模态数据融合：为了完成多模态数据融合，首先利用VGG16网络和cifar10数据集完成多输入网络的分类，在VGG16的基础之上，将前三层特征提取网络作为不同输入的特征提取网络，在中间层进行特征拼接，后面的卷积层用于提取融合特征，最后加上全连接层。该网络稍作修改就能同时提取两张对应的图片作为输入，在特征提取之后进行融合用于分类。

Language:PythonBSD-2-Clause7700

diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

Language:PythonApache-2.02561400

LAVIS

LAVIS - A One-stop Library for Language-Vision Intelligence

Language:Jupyter NotebookBSD-3-Clause979400

GroundingDINO

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

Language:PythonApache-2.0655000

Grounded-Segment-Anything

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

Language:Jupyter NotebookApache-2.01496800

RMDL

RMDL: Random Multimodel Deep Learning for Classification

Language:PythonGPL-3.042300

DALLE2-pytorch

Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch

Language:PythonMIT1110900

stable-diffusion

A latent text-to-image diffusion model

Language:Jupyter NotebookNOASSERTION6798100

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

MIT598400

WordArt

The official code of CornerTransformer (ECCV 2022, Oral) on top of MMOCR.

Language:PythonApache-2.013700

opencv_3rdparty

OpenCV - 3rdparty

NOASSERTION34000

leetcode

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

Language:JavaScriptNOASSERTION5461600

Cell-Nuclei-Detection-and-Segmentation

Detect location and draw boundary of nuclei from microscopic images

Language:Python7200

detect-cell-edge-use-unet

Unet

Language:PythonGPL-2.013500

awesome-cell-detection-segmentation

nucleus/cell and histopathology image classification,detection,segmentation

GPL-3.025300

TableMASTER-mmocr

2nd solution of ICDAR 2021 Competition on Scientific Literature Parsing, Task B.

Language:PythonApache-2.043100

CRAFT-Reimplementation

CRAFT-Pyotorch：Character Region Awareness for Text Detection Reimplementation for Pytorch

Language:Python46400

tableImageParser_tx

table structure recognition

Language:Python27000

PytorchOCR

基于Pytorch的OCR工具库，支持常用的文字检测和识别算法

Language:Python137500

DeepLearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

Language:JavaScriptGPL-3.05463300

deep-text-recognition-benchmark

Text recognition (optical character recognition) with deep learning methods, ICCV 2019

Language:Jupyter NotebookApache-2.0373700

awesome-deep-text-detection-recognition

A curated list of resources for text detection/recognition (optical character recognition ) with deep learning methods.

Apache-2.0251200

Character-Region-Awareness-for-Text-Detection-

https://arxiv.org/abs/1904.01941

Language:Python12400

kbqa

基于知识库的问答：seq2seq模型实践

Language:Python35600

ccks2019-ckbqa-4th-codes

中文知识库问答代码，CCKS2019 CKBQA评测第四名解决方案

Language:Python47700

gAnswer

A KBQA system based on DBpedia.

Language:JavaBSD-3-Clause37600

tensorflow-image-classification

CNN for multi-class image recognition in tensorflow

Language:Jupyter Notebook39300

image-classification-CIFAR10-tf

Simple Image Classification Models for the CIFAR-10 dataset using TensorFlow

Language:PythonMIT15200

QASystemOnMedicalGraph

该项目是基于医疗领域知识图谱的问答系统。实现比较简单。

Language:Python125100

KGQA_insurance_product

基于开源保险产品数据构建的保险知识图谱及简易问答系统

Language:PythonMIT3300