[7] Belhassen Bayar and Matthew C Stamm. A deep learn-ing approach to universal image manipulation detectionusing a new convolutional layer. In ACM Workshop onInformation Hiding and Multimedia Security, 2016. [8] Belhassen Bayar and Matthew C Stamm. Constrainedconvolutional neural networks: A new...
Consequently, traditional compression methods like Huffman coding and DPCM are not suitable for this task. Deep autoencoders, renowned for their adeptness at learning data features, offer a promising alternative. By leveraging their capability to extract key features from high-dimensional data and ...
We propose a deletion based approach to sentence compression using LSTM, where SC is modeled as a two-class classification problem and the task is to decide whether a word of a sentence to be retained or to be removed based on its context like previous and next words in the sequence. ...
内容提示: 1ADMM-CSNet: A Deep Learning Approach forImage Compressive SensingYan Yang, Jian Sun ∗ , Huibin Li, and Zongben XuAbstract—Compressive sensing (CS) is an effective technique for reconstructing image from a small amount of sampled data. It hasbeen widely applied in medical imaging...
A deep-learning method for evaluating shaft resistance of the cast-in-site pile on reclaimed ground using field data 基于现场试验的复垦地层灌注桩侧摩阻力的深度学习评价方法 Sheng-liang Lu, Ning Zhang, Shui-long Shen, Annan Zhou, Hu-zhong Li ...
Based on the success of deep neural networks for image recovery, we propose a new paradigm for the compression and decompression of ultrasound (US) signals which relies on stacked denoising autoencoders. The first layer of the network is used to compress the signals and the remaining layers per...
and it is able to adaptively handle the various patterns of stripes and even artifacts existed in the stitched fluorescence images. In contrast to previous deep learning-based shading correction methods, SSCOR can be applied in situations where there is insufficient training data with only one or ...
However, few existing methods take an end-to-end approach of composing compressions with system optimizations, as it requires significant efforts to bring modeling, algorithm, and system areas of deep learning to work synergistically together. DeepSpeed Compression overcomes these chall...
breast tomosynthesis (DBT) images to facilitate the development and evaluation of artificial intelligence algorithms for breast cancer screening; to develop a baseline deep learning model for breast cancer detection; and to test this model using the data set to serve as a baseline for future ...
为了倡导基于深度学习的视频编码研究,本文对我们开发的视频编解码器即深度学习视频编码(Deep Learning Video Coding,DLVC)进行了案例研究。DLVC具有两个深度工具,分别为基于CNN的环路滤波器(CNN-based in-loop filter,CNN-ILF)以及基于CNN的块自适应分辨率编码(CNN-based block adaptive resolution coding,CNN-BARC)。