نتایج جستجو برای: deep learning

تعداد نتایج: 755011  

2016
Vanika Singhal Anupriya Gogna Angshul Majumdar

A recent work introduced the concept of deep dictionary learning. The first level is a dictionary learning stage where the inputs are the training data and the outputs are the dictionary and learned coefficients. In subsequent levels of deep dictionary learning, the learned coefficients from the previous level acts as inputs. This is an unsupervised representation learning technique. In this wo...

2016
Zewang Zhang Zheng Sun Jiaqi Liu Jingwen Chen Zhao Huo Xiao Zhang

A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, w...

Journal: :CoRR 2017
Weilin Xu David Evans Yanjun Qi

Feature squeezing is a recently-introduced framework for mitigating and detecting adversarial examples. In previous work, we showed that it is effective against several earlier methods for generating adversarial examples. In this short note, we report on recent results showing that simple feature squeezing techniques also make deep learning models significantly more robust against the Carlini/W...

Journal: :CoRR 2015
Heechul Jung Sihaeng Lee Sunjeong Park Injae Lee Chunghyun Ahn Junmo Kim

Temporal information can provide useful features for recognizing facial expressions. However, to manually design useful features requires a lot of effort. In this paper, to reduce this effort, a deep learning technique which is regarded as a tool to automatically extract useful features from raw data, is adopted. Our deep network is based on two different models. The first deep network extracts...

Journal: :CoRR 2017
Jingchun Cheng Sifei Liu Yi-Hsuan Tsai Wei-Chih Hung Shalini De Mello Jinwei Gu Jan Kautz Shengjin Wang Ming-Hsuan Yang

We propose a deep learning-based framework for instance-level object segmentation. Our method mainly consists of three steps. First, We train a generic model based on ResNet-101 for foreground/background segmentations. Second, based on this generic model, we fine-tune it to learn instance-level models and segment individual objects by using augmented object annotations in first frames of test v...

2013
Stellan Ohlsson

Preparing the books to read every day is enjoyable for many people. However, there are still many people who also don't like reading. This is a problem. But, when you can support others to start reading, it will be better. One of the books that can be recommended for new readers is deep learning how the mind overrides experience. This book is not kind of difficult book to read. It can be read a...

Journal: :CoRR 2018
Aneta Neumann Christo Pyromallis Bradley Alexander

Evolutionary search has been extensively used to generate artistic images. Raw images have high dimensionality which makes a direct search for an image challenging. In previous work this problem has been addressed by using compact symbolic encodings or by constraining images with priors. Recent developments in deep learning have enabled a generation of compelling artistic images using generativ...

2006
Michael A. Ringenberg Kurt VanLehn

This study seeks to compare the relative utility for learning college-level physics of intelligent tutoring systems that have procedural based hints and worked-out examples. In order to test which produced better gains, a modified version of Andes was used in which participants either received hints or annotated, worked-out examples in response to their help requests. We found that providing an...

Journal: :CoRR 2017
Ayan Sinha Justin Lee Shuai Li George Barbastathis

1Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 2Institute for Medical Engineering Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 3Singapore-MIT Alliance for Research and Technology (SMART) Centre, One Create Way, Singapore 117543, Singapore *Corresponding author: sinhayan@mi...

Journal: :CoRR 2017
Hao Jiang

In view of the fact that biological characteristics have excellent independent distinguishing characteristics,biometric identification technology involves almost all the relevant areas of human distinction. Fingerprints, iris, face, voice-print and other biological features have been widely used in the public security departments to detect detection, mobile equipment unlock, target tracking and...

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