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深度学习常用损失函数的基本形式、原理及特点
【实例简介】深度学习常用损失函数的基本形式、原理及特点
- 2022-01-19 00:31:50下载
- 积分：1
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Evaluate_J.py
说明： 含界面的CT试件的J积分计算。计算了（Simha，N.K.等人2005）的结果。主要是提取界面上的材料力，对J积分进行修正以保持路径无关性。(J integral for compact tension specimen with interface. The results of (Simha, N.K. et al 2005) are reproduced. Mainly, the material force in the interface is extracted and the J-integral is corrected to retain path independence.)
- 2021-04-08 17:19:00下载
- 积分：1
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checker
英国国际跳棋（英国英语）或跳棋（美国英语、加拿大英语），又称美国跳棋或直棋，是一种棋盘游戏棋。它是在一个8×8方板（共六十四平方）每侧有十二块。棋子的移动和捕获对角。他们可能只前进直到他们到达的板的另一端，当他们加冕，然后可以移动和捕获的向后和向前的。(English draughts (British English) or checkers (American English and Canadian English), also called American checkers or Straight checkers, is a form of the board game draughts. It is played on an 8×8 square board (with sixty-four total squares) with twelve pieces on each side. The pieces move and capture diagonally. They may only move forward until they reach the opposite end of the board, when they are crowned and may thereafter move and capture both backward and forward.)
- 2013-05-18 23:18:02下载
- 积分：1
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车牌识别
【实例简介】
- 2021-07-12 00:31:49下载
- 积分：1
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homework_SVM.py
实现支持向量机SVM算法，用于iris分类，包括用cvxopt进行优化(Implement SVM algorithm for iris classification, including cvxopt optimization)
- 2018-12-25 23:43:05下载
- 积分：1
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word-language-model
说明： 自然语言处理, Python編程語言的自然語言處理工具包(Natural language processing, RNN model)
- 2019-11-27 01:56:39下载
- 积分：1
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trees
说明： 决策树分类，机器学习算法需要作用于数据，数据的属性和特征决定了机器学习算法是否适用，同时，数据质量的好坏也直接决定算法表现的好坏。这篇博客选择在Adult数据集上进行实验。(Decision tree classification)
- 2020-07-04 11:23:26下载
- 积分：1
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chatbotv5
说明： 自然语言理解，中文人机对话系统。。。。。。(Natural language understanding, Chinese man machine dialogue system)
- 2020-06-16 10:43:45下载
- 积分：1
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pggan-pytorch
说明： 渐进的让生成器和判别器增长：从一个低分辨率开始，随着训练发展，不断添加新层使模型增加更好的细节。(Let the generator and discriminator grow gradually: start with a low resolution and add new layers to the model with the development of training.)
- 2021-04-18 13:28:57下载
- 积分：1
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svm解析验证码
SVM做的验证码识别，准确率85%# -*- coding: utf-8 -*
__author__ = "eple"
from svmutil import *
from PIL import Image
from numpy import *
import os
import string
def getFeatures(path):
features = []
im = array(Image.open(path).convert("L"))
h,w = shape(im)
for i in xrange(0,h):
for j in xrange(0,w):
im[i][j] = 0 if im[i][j] < 128 else 1
for i in xrange(1,h-1):
for j in xrange(1,w-1):
if im[i][j] != 0 and im[i-1][j]==0 and im[i][j-1]==0 and im[i][j+1]==0 and im[i+1][j]==0:
im[i][j] = 0
for rang in [xrange(2,8), xrange(12,18), xrange(22,28), xrange(32,38)]:
temp = []
for i in rang:
for j in xrange(0,10):
temp.append(im[j][i])
features.append(temp)
return features
- 2022-04-14 17:07:19下载
- 积分：1
