Using Arduino as a front end to detect temperature as a streaming data goining MQTT and through Spark streaming for a near realtime process back to mysql database.
Also provide another Arduino lighting on if the counting measure is over than threshold for a realtime experiment case.
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Se...郁凱 黃
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning
- Author: Xiaoxiao Guo, Satinder Singh, Honglak Lee, Richard L. Lewis, Xiaoshi Wang
- Origin: https://papers.nips.cc/paper/5421-deep-learning-for-real-time-atari-game-play-using-offline-monte-carlo-tree-search-planning
- Related: https://github.com/number9473/nn-algorithm/issues/251
Human-level control through deep reinforcement learning郁凱 黃
Human-level control through deep reinforcement learning
- Author: Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg & Demis Hassabis
- Origin: https://www.nature.com/articles/nature14236
- https://github.com/number9473/nn-algorithm/issues/252
Ring loss: Convex Feature Normalization for Face Recognition郁凱 黃
Ring loss is a feature normalization approach for deep networks that augments standard loss functions like softmax. It encourages the norm of sample features to be a learned parameter R rather than enforcing hard normalization. This soft normalization helps address issues with imbalanced classification margins and disconnect between training and testing metrics due to variation in feature norms. Experiments on large face recognition datasets show Ring loss improves performance compared to softmax, especially for low resolution images where feature norms are typically lower. It achieves state-of-the-art results on benchmarks like LFW, IJB-A, MegaFace, and CFP.
Playing Atari with Deep Reinforcement Learning郁凱 黃
Playing Atari with Deep Reinforcement Learning
- Author: Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller
- Origin: https://arxiv.org/abs/1312.5602
- Related: https://github.com/number9473/nn-algorithm/issues/250
A Revisit of Feature Learning on CNN-based Face Recognition郁凱 黃
A Revisit of Feature Learning on CNN-based Face Recognition.
Y. Sun, X. Wang, and X. Tang. Deep learning face representation from predicting 10,000 classes. In CVPR , 2014.
K. He, X. Zhang, S. Ren, J. Sun. Deep Residual Learning for Image Recognition.
Y. Sun, X. Wang, X. Tang. Deep Learning Face Representation by Joint Identification-Verification.
F. Schroff, D. Kalenichenko, J. Philbin. FaceNet: A Unified Embedding for Face Recognition and Clustering.
Y. Wen, K. Zhang, Z. Li, Y. Qiao. A Discriminative Feature Learning Approachg.
W. Liu, Y. Wen, Z. Yu, M. Yang. Large-Margin Softmax Loss for Convolutional Neural Networks.
W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, L. Song. SphereFace: Deep Hypersphere Embedding for Face Recognition.
Topic: design a puzzle game on smart phone
Akatsuki Hackthon 2015 心得: http://joyhuang9473.github.io/2015/09/07/akatsuki-hackathon-2015.html
Our Work - Ginger & GingerMan: http://joyhuang9473.github.io/project-general/project-game/2015/09/05/project-ginger-and-gingerman.html
This document provides an introduction and outline for a presentation on FreeBSD commands. It discusses how FreeBSD is Unix-like and provides an overview of commands related to users, networking, file ownership and access permissions. As an example, it demonstrates how to use the cp command to copy a file, listing the original file, running the cp command, and then listing both the original and copied file.
21. Username: egg
Full name: egg
Uid (Leave empty for default ):
Login group [egg]:
Login group is egg. Invite egg into other
groups? [ ]:
Login class [default]:
Shell (sh csh tcsh nologin) [sh]: csh
Home directory [/home/egg]:
Home directory permissions (Leave empty for
default):
Use password-based authentication? [yes]:
Use an empty password? (yes/no) [no]:
Use a random password? (yes/no) [no]:
Enter password:
Enter password again:
Lock out the accout after creation? [no]:
Username
: egg
Password
: *****
..
/
Home
Group
30. egg@:/var % cd /
egg@:/ % ls
COPYRIGHT
bin
boot
dev
entropy
etc
home
lib
libexec
media
mnt
proc
rescue
root
sbin
sys
tmp
usr
var
entropy
etc
home
lib
libexec
media
mnt
proc
rescue
root
sbin
sys
tmp
usr
var
egg@:/ % ls -a
.
..
.cshrc
.profile
.snap
.sujournal
COPYRIGHT
bin
boot
dev
