artificial-intelligence

问题 I'm new to the concept of ROC curves . I've tried to understand it by reading a few tutorials on the web. I found a really good example here in python which was helpful. I want to plot a ROC curve for multiclass classifier that I built(in Python). However, Most of the solutions on the web are for 2 class problems and not multiclass . However, I finally found "multiclass.roc" function in pROC package in R which does multiclass ROC curve plotting. The following is a simple example: library(pROC

问题 I've been involved with a lot of C-Programming and RT-Linux, now I want to do some Artificial Neural Networking. BUT: How do I get started? I'm also very interested in Evolutionary Algorithms(Learning Algorithms) and Artificial Intelligence. Where can I start learning all of this? 回答1: If you're just trying to get familiar with AI, then I would recommend that you take the Stanford's free online courses: https://www.ai-class.com/ http://www.ml-class.org/course/auth/welcome Get a good

问题 I've been involved with a lot of C-Programming and RT-Linux, now I want to do some Artificial Neural Networking. BUT: How do I get started? I'm also very interested in Evolutionary Algorithms(Learning Algorithms) and Artificial Intelligence. Where can I start learning all of this? 回答1: If you're just trying to get familiar with AI, then I would recommend that you take the Stanford's free online courses: https://www.ai-class.com/ http://www.ml-class.org/course/auth/welcome Get a good

问题 I am trying to build a customized ANN Model on Python. My method, where I have built the model, is as follows: def binary_class(x_train,nodes,activation,n): #Creating customized ANN Model model=Sequential() for i in range(len(nodes)): if(i==0): if(activation=='sigmoid'): model.add(Dense(units = nodes[i], kernel_initializer = 'glorot_uniform',activation='sigmoid',input_dim = len(x_train[1]))) if(activation=='relu'): model.add(Dense(units = nodes[i], kernel_initializer = 'he_uniform',activation

问题 I am writing a code on Jupyter notebook using python to recognize the number on the device with 7segment(FND). I used opencv and got the edge of the image. import cv2 import matplotlib.pyplot as plt def detect_edge(image): ''' function Detecting Edges ''' image_with_edges = cv2.Canny(image , 100, 200) images = [image , image_with_edges] location = [121, 122] for loc, img in zip(location, images): plt.subplot(loc) plt.imshow(img, cmap='gray') plt.savefig('edge.png') plt.show() image = cv2

问题 Getting the following error message when setting up a 3D-GAN for ModelNet10: InvalidArgumentError: Input to reshape is a tensor with 27000 values, but the requested shape has 810000 [Op:Reshape] In my opinion the batch is not properly created and thereby the shape of the tensor is not valid. Tried different things but can´t get the batch set up.. I am more than thankful for any hints how to clean up my code! Thanks in advance! import time import numpy as np import tensorflow as tf np.random

问题 I am working on a classification problem using CNN where my input image size is 64X64 and I want to use pretrained model such as VGG16 , COCO or any other. But the problem is input image size of pretrained model is 224X224 . How do I sort this issue. Is there any data augmentation way for input image size. If I resize my input image to 224X224 then there is very high chance of image will get blurred and that may impact the training. Please correct me if I am wrong. Another question is related

问题 I try to implement beam collision detection with a predefined track mask in Pygame. My final goal is to give an AI car model vision to see a track it's riding on: This is my current code where I fire beams to mask and try to find an overlap: import math import sys import pygame as pg RED = (255, 0, 0) GREEN = (0, 255, 0) BLUE = (0, 0, 255) pg.init() beam_surface = pg.Surface((500, 500), pg.SRCALPHA) def draw_beam(surface, angle, pos): # compute beam final point x_dest = 250 + 500 * math.cos

问题 Hi i tried to write a code, where i write a number on the screen with pygame and then a neural Network predicts the number i wrote. My problem is that i trained my neural network with image arrays in a (28, 28, 3). So i tried to reshape my (280, 280, 3) array. but when i do so my array is None. I use Python 3.7 string_image = pygame.image.tostring(screen, 'RGB') temp_surf = pygame.image.fromstring(string_image, (280, 280), 'RGB') array = pygame.surfarray.array3d(temp_surf) array = array

问题 I am attempting to predict the ideal move in a game using a keras sequential network. The network is fairly simple with (what I think to be) an input shape of (3216,). The code for defining the network is attached bellow. self.model = keras.Sequential() self.model.add(Dense(2000, activation='relu', input_dim=(2 * 7 + 2 + Cfg.tiles_x * Cfg.tiles_y))) self.model.add(Dense(1000, activation='relu')) self.model.add(Dense(100, activation='relu')) self.model.add(Dense(9)) self.model.compile(loss