Caffe | Fine-tuning for style recognition
Fine-tuning CaffeNet for Style Recognition on “Flickr Style” Data Fine-tuning takes an already learned model, adapts the architecture, and resumes training from the already learned model weights. Let’s fine-tune the BAIR-distributed CaffeNet model on a different dataset, Flickr Style, to predict image style instead of object category. Explanation The Flickr-sourced images of the Style dataset are
Deep Gate Recurrent Neural Network
This paper introduces two recurrent neural network structures called Simple Gated Unit (SGU) and Deep Simple Gated Unit (DSGU), which are general structures for learning long term dependencies. Compared to traditional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), both structures require fewer parameters and less computation time in sequence classification tasks. Unlike GRU and LSTM
About – All Prior Art
All Prior Art is a project attempting to algorithmically create and publicly publish all possible new prior art, thereby making the published concepts not patent-able. The concept is to democratize ideas, provide an impetus for change in the patent system, and to preempt patent trolls. The system works by pulling text from the entire database of US issued and published (un-approved) patents and cr
成長し続けるディープラーニングを制するのは誰か - BRIDGE（ブリッジ）
via Flickr by “A Health Blog“. Licensed under CC BY-SA 2.0. Amit Karp氏はBessemer Venture Partnersの副社長である。彼は同社イスラエル事務所で勤務しており、イスラエルとヨーロッパにおける投資に焦点をあてている。彼をTwitterでフォローしよう。@amitkarp via Flickr by “Jiuguang Wang“. Licensed under CC BY-SA 2.0. 人工知能（AI）*は私たちの予想をはるかに超えて急速に発達している。先月、GoogleのDeepMind AIが伝説的囲碁棋士のLee Sedol氏に勝利したことは業界にとって決定的な瞬間だった。この勝利を手にしたのは、ディープラーニングと呼ばれる比較的新しい人工知能技術で、人工知能に変革をもたらしているものだ。 ディー
Aylien launches news analysis API powered by its deep learning tech | TechCrunch
Aylien launches news analysis API powered by its deep learning tech Text analysis startup Aylien, which uses deep learning and NLP algorithms to parse text and extract intel from documents for its customers, has launched a new tool specifically focused on analyzing written news content. “The idea for the News API is to give access to the news content that is out there enriched and in real-time to
Learning to Answer Questions From Image Using Convolutional Neural Network
In this paper, we propose to employ the convolutional neural network (CNN) for the image question answering (QA). Our proposed CNN provides an end-to-end framework with convolutional architectures for learning not only the image and question representations, but also their inter-modal interactions to produce the answer. More specifically, our model consists of three CNNs: one image CNN to encode t
ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering
We propose a novel attention based deep learning architecture for visual question answering task (VQA). Given an image and an image related natural language question, VQA generates the natural language answer for the question. Generating the correct answers requires the model's attention to focus on the regions corresponding to the question, because different questions inquire about the attributes
数学的基礎から学ぶ Deep learning (with Python) Vol. 4【MPS 横浜 第4回】
MPS横浜 概要 MPSは、「みんなでわいわいソフトウェア作りながら技術を磨いて実績を作ろう!」をコンセプトに活動しています。プログラミング玄人とも初心者もみんなで協力して作品作りを行い、できあがった作品は共同制作のオープンソース・ソフトウェアとして、世の中に出します。 MPS横浜は「筋電位とDeep learning を用いた簡単なロボットアームを作ってみよう!」をテーマに発足しました。 前回から数回にわたって行う勉強会は、そのための Deep learning と電子回路に関する知識の実践的な獲得を目的とします。前提知識をあまり仮定せず 、基礎の基礎から学べるようにしてゆきます (高校二年生程度の数学の知識と if や for 文など Python の経験を少し仮定しますが、なくても是非チャレンジしてみてください ! )。 勉強会の後はみんなでご飯を食べにいきます ! 今回の予定 数学
Amazonが ディープラーニングスタートアップ Orbeus を買収 - BRIDGE（ブリッジ）
via Flickr by “A Health Blog“. Licensed under CC BY-SA 2.0. via Flickr by “Wonderlane“. Licensed under CC BY-SA 2.0. ＜ピックアップ＞Amazon hires team behind deep learning startup Orbeus Amazon は、写真や動画内の人物や物を人工知能の一種であるディープラーニングを用いて特定する技術を開発する小さなスタートアップ Orbeusで働くメンバーのほぼ全員を雇用した。Orbeusは、PhotoTimeと呼ばれる瞬時に写真にタグをつけられるiOSとAndroidアプリや、開発者が自身のアプリに使えるRekognition APIを開発している。 Orbeus のCEO Yi Li氏とAmazonは本件についてコメントをしておら
Deep learning driven jazz generation
Using Keras & Theano for deep learning driven jazz generation Download .zip Download .tar.gz Using Keras & Theano for deep learning driven jazz generation I built deepjazz in 36 hours at a hackathon. It uses Keras & Theano, two deep learning libraries, to generate jazz music. Specifically, it builds a two-layer LSTM, learning from the given MIDI file. It uses deep learning, the AI tech that powers
Chess position evaluation with convolutional neural network in Julia
In this post we will try to challenge the problem of chess position evaluation using convolutional neural network (CNN) – a neural network type designed to deal with spatial data. We will first explain why we need CNNs then we will present two fundamental CNN layers. Having some knowledge from the inside of the black box, we will apply CNN to the binary classification problem of chess position eva
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
DIY Deep Learning for Vision: a Hands-On Tutorial with Caffe
Research data supporting “PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization”: Kings College
GitHub - jazzsaxmafia/Weakly_detector: Tensorflow implementation of "Learning Deep Features for Discriminative Localization"
Learning Deep Features for Discriminative Localization | GitXiv
GitHub - yujiosaka/js-mind: Deep Learning Library Written in ES2015.
A Convolutional Neural Network Neutrino Event Classifier
深層学習フレームワークChainerの勉強に役立つページのまとめ - Qiita
TechCrunch | Startup and Technology News
NVIDIA DGX Platform
