[PDF] Top 20 Dense convolutional networks for efficient video analysis
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Dense convolutional networks for efficient video analysis
... For video classification problems, there are some generally accepted algorithm based on deep learning method [8, ...recurrent networks are also a good approach to extract temporal relation between frames ... See full document
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Convolutional neural networks for efficient object detection on ultra low-power platforms
... smart analysis is in many cases based on convolutional neural networks as the fundamental tool to extract features and information out of various raw data ... See full document
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1. Efficient face recognition using convolutional neural networks
... component analysis and similarly video based biometric person authentication are suggested in [11,12,14,15] ,The best learning algorithms using convolutional networks are presented in Lecun ... See full document
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Energy-Efficient User Association In Extremely Dense Small Cell Networks
... the analysis of capacity in terms of UEs’s average throughput (Mb/s) and on the eNBs network power consumption ...the analysis is to highlight the gains introduced by a wise association of the UEs to the ... See full document
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An Analysis of Convolutional Neural Networks for detecting DGA
... LSTM networks have proved to be diffi- cult to train under some particular cases ...LSTM networks in DGA ...technique: Convolutional Neural Networks ...neural networks that use ... See full document
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MEA: an energy efficient algorithm for dense sector based wireless sensor networks
... sensor networks is analytically ...energy efficient algorithm for these networks which is called minimum energy algorithm ...detailed analysis verifies that the proposed algorithm has the ... See full document
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Recurrent Fully Convolutional Networks Based on Optical Flow for Video Eyes Fixation Prediction
... of video content analysis ...semantic analysis, target tracking, object segmentation and other aspects ...the video can effectively assist people in video analysis ... See full document
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An efficient and high-resolution topology optimization method based on convolutional neural networks
... an efficient and high-resolution topology optimization method is proposed based on the Super-Resolution Convolutional Neural Network (SRCNN) technique in the framework of ...element analysis (FEA) ... See full document
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Aspect Based Sentiment Analysis with Gated Convolutional Networks
... sentiment analysis (ABSA) can provide more detailed information than general sentiment analysis, because it aims to predict the sentiment polarities of the given aspects or entities in ...sentiment ... See full document
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Stereoscopic video quality assessment based on 3D convolutional neural networks
... raw video is split in both spatial and temporal dimensions, re- sulting in numerous low-resolution short video ...cubic video patch is set as 10 × 32 × 32, namely 10 frames with a resolution of 32 × ... See full document
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Recognizing Microscopic Structures: Dense Semantic Segmentation of Multiple Histopathological Classes using Fully Convolutional Neural Networks
... neural networks are a subclass of ...image analysis, only two- dimensional filters are relevant for the convolutions, though the filter dimen- sionality can be arbitrarily large in ...the ... See full document
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Preliminary Study on the Efficient Electrohysterogram Segments for Recognizing Uterine Contractions with Convolutional Neural Networks
... measurement has been considered a noninvasive method and an alternative approach of TOCO to monitor UC [5]. EHG features have been investigated to distinguish between UCs and non-UCs (non-uterine contractions) [6, 7]. ... See full document
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A Parameter-Efficient Deep Dense Residual Convolutional Neural Network for Volumetric Brain Tissue Segmentation from Magnetic Resonance Images
... neural networks are currently the preferred methods for the segmentation of brain tissues from MR ...are efficient at abstracting high and low-level representations of data by learning important features at ... See full document
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Efficient and Robust Methods for Audio and Video Signal Analysis
... neural networks utilize feed-back loops, which enable them to model de- pendencies among consecutive inputs (Haykin ...(LSTM) networks (Hochreiter and Schmidhuber (1997)) have shown to provide excellent ... See full document
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Deformable Convolutional Networks Tracker
... In computer vision, object tracking (also known as visual tracking) has always been an important topic. Visual tracking determines the motion information, direction and trajectory of the target by estimating the ... See full document
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Efficient Convolutional Neural Networks for Diacritic Restoration
... ative analysis of models’ training and inference runtime (Table ...its efficient performance es- pecially for industrial settings where time is a cru- cial ... See full document
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Spatial effects of video compression on classification in convolutional neural networks.
... towards video analysis, and large video datasets already include YouTube-8M [4], Sport1M [5] and ImageNet’s expanding video dataset ...to video applications without ...both video ... See full document
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On the efficient utilization of radio resources in extremely dense wireless networks
... wireless networks, the instantaneous channel quality of users varies significantly in a ...a dense network, getting accurate feedbacks and processing them for a large number of users imposes high overhead ... See full document
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Energy Efficient Resource Sharing and Scheduling for Video over Wireless Networks
... in video coding technologies together with the rapid developments of network infrastructures as well as the exponential growth in storage capacity and computing power, an increasing number of video ... See full document
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Exploring Convolutional Neural Networks for Sentiment Analysis of Spanish tweets
... Instead of using bag-of-words (BoW) to repre- sent tweets, we exploited word embedding rep- resentation. A word embedding is a function to map words to low dimensional vectors, which are learned from a large collection ... See full document
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