機器視覺雜話(ZA WARUDO)

from :  https://www.krizna.com/ubuntu/setup-file-server-ubuntu-14-04-samba/ Setup File server on ubuntu 14.04 ( Samba ) November 18, 2014   krizna   Ubuntu ,  Ubuntu 14.04   7 Samba  is a free software used to enable file and print services on unix-like systems. It runs on most unix variants, such as Linux, AIX, Solaris and BSD. This article helps you to set up file server on ubuntu 14.04 server. This article contains steps for creating both anonymous ( without username and password ) and secured shares . 1.  Anonymous share . 2.  Secured share . 3.  User creation . Setup File server on ubuntu 14.04 Step 1 »  Install samba packages after updating repositories krizna@leela:~$ sudo apt-get update krizna@leela:~$ sudo apt-get install samba samba-common python-glade2 Creating Anonymous share Everyone can access and store files without username and password . Step 2 »  Create folder for Anonymous share. krizna@le...

使用gdisk指令： sudo gdisk  /dev/sdx (x為你的partition 代號) GPT fdisk (gdisk) version 1.0.1 Partition table scan: MBR: MBR only BSD: not present APM: not present GPT: not present *************************************************************** Found invalid GPT and valid MBR; converting MBR to GPT format. THIS OPERATION IS POTENTIALLY DESTRUCTIVE! Exit by typing 'q' if you don't want to convert your MBR partitions to GPT format! ************************************************************** MBR 轉 GPT Enter  w  to write GPT partition on disk. Press  y  to confirm your choice. GPT 轉 MBR Enter  r  to enter in  recovery and transformation options . Enter  g  to convert GPT to MBR partition. 注意：如果是開機碟，boot loader會消失。要重新設定將這個磁碟轉為可開機 讓你的 磁碟轉為 bootable 可開機 第一，確定你的磁碟第一partition空間必須要支援開機，使用 fdisk -l 可以顯示第一個partition開始自2048，如下：   spp1@my_ubuntu:~$ sudo fdisk -l /dev/sda [...] Device Boot Start End Sectors Size Id...

ubuntu 以下2個指令可以安裝 program that 可將.nrg檔案轉換為.iso sudo apt-get install nrg2iso sudo apt install iat nrg2iso常無法使用, 而iat通常可用： 轉換指令如下： nrg2iso image.nrg image.iso iat image.nrg image.iso

以下是從2014-2017年間機器學習與深度學習論文引用最高的前20大((top 20 papers machine learning and Deep Learning in 2014 to 2017))： The criteria we used to select the 20 top papers are by using citation counts from three academic sources:  scholar.google.com ;  academic.microsoft.com ; and   semanticscholar.org . Since the number of citations varied among sources and are estimated, we listed the results from  academic.microsoft.com  which is slightly lower than others. For each paper we also give the year it was published, a Highly Influential Citation count (HIC) and Citation Velocity (CV) measures provided by   semanticscholar.org .  HIC that presents how publications build upon and relate to each other is result of identifying meaningful citations. CV is the weighted average number of citations per year over the last 3 years. For some references, where CV is zero that means it was blank or not shown by  semanticscholar.org . Most (but not all) of ...