sherlock1987 Goto Github PK

-fire-recognition

In this project, a fire extinguishing control system based on computer vision recognition is designed, which uses single chip computer as the control module of the car, PC and camera as the fire source identification and image processing module. Compared with PC, MCU can give full play to its advantages, output PWM wave to control the speed of the motor, and then control the overall movement of the car; PC can also play its powerful computing skills, showing the image of the fire source after processing. The fire extinguishing car mainly consists of power supply circuit, motor drive circuit, fire extinguishing device, single chip control circuit, and the overall framework of the car. The power supply circuit is used to provide the working power needed by the system. The driving chip drives the motor to control the movement of the car and the fire extinguishing device to extinguish the fire. The main work process of this design is: firstly, the data is transmitted to PC through camera. PC uses OPENCV library function and VISUAL STUDIO software to process the data, identify the flame position, and mark it on the image with rectangular box. After finding the fire source, the action signal is transmitted to the single-chip computer. Finally, the single-chip computer controls the movement of the car according to the established procedures and the specific commands of the PC, and completes a series of fire fighting actions.

a-vehicle-collision-rescuing-system

abc-fusion

absa-pytorch

Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。

ae-lstm

We proposes an Attention-Encoded LSTM, which is Multi Head Self Attention based so that it will eschews the relationship between context and target.

awesome-chatgpt-aigc-lesson

关于ChatGPT，以及AIGC的学习道路，里面包含的内容很多，有语言模型，还有RLHF，多模态论文等等，本人的公众号是船长尼莫，感兴趣可以关注一下~

chatglm-6b

ChatGLM-6B：开源双语对话语言模型 | An Open Bilingual Dialogue Language Model

convlab

DSTC8 Track 1 Task 1 End-to-End Multi-Domain Dialog Challenge Result:

convlab-2

ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems

crosslingual-slu

EMNLP-2020: Cross-lingual Spoken Language Understanding with Regularized Representation Alignment

deepctr-torch

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

dp-without-adv

Guided dialogue policy learning without adversarial learning in the loop

ecspell

gdpl

Task-oriented Dialog Policy Learning with Adversarial Inverse Reinforcement Learning

github-markdown-toc

Easy TOC creation for GitHub README.md

imitation-learning-paper-lists

Paper Collection for Imitation Learning in RL.

inverse_rl

The whole code is runing on the platform of pydial. Please download the code and run the experiment.

kaggle_great-energy-predictor

kmodes

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

leetcode

part of my personal coding for Leetcode

leetcode_tag

Python Solutions for Leetcode

leetcodetop

汇总各大互联网公司容易考察的高频leetcode题🔥

masp

mathemtical-pattern-recongnition

codes work from course

mt-with-gan

Adversarial Training or Generative Adversarial Networks have shown great promise in Image Generation and are able to achieve state-of-the-art results. However, For sequential data such as text, training GANs has proven to be difficult. One reason is because of non-differentiable nature of generating text with R NNs. Consequently, there have been past work where GANs have been employed for NLP tasks such as text generation, sequence labelling, etc. As a part of directed research, I examine one such application of GAN with RNN called Adversarial Neural Machine Translation.

multilingual-zeroshot-slotfilling

nlper-interview

该仓库主要记录 NLP 算法工程师相关的面试题

opennmt-py

Open Source Neural Machine Translation in PyTorch

project_ee599

This is a course project of EE599, related to graph computing and serarching.

pytorch-gan

PyTorch implementations of Generative Adversarial Networks.