paper, we propose a method, namely CNN-S, to improve training efficiency and cost based on Storm and is suitable for every algorithm. This model divides data into several sub sets and processes data on several machine in parallel flexibly. The experimental results show that in the case of ...
Speechmatics’ paper was submitted and accepted to the most prestigious ML conference – NeurIPs. The paper is about a type of lossy image compression algorithm based on discrete representation learning, leading to a system that can reconstruct images of high-perceptual quality and retain semantically ...
In this paper we introduce Principal Filter Analysis (PFA), an easy to use and effective method for neural network compression. PFA exploits the correlation between filter responses within network layers to recommend a smaller network that maintain as much as possible the accuracy of the full model...
Then, the classification model is trained by TextCNN. The experiment shows that the algorithm in this paper can get good classification effect, the highest F1 value can reach 95.07%. For the problem of difficult classification of other category, four different classification methods are compared. ...
In this paper, Baidu researchers propose PCW-Net, a Pyramid Combination and Warping cost volume-based network, which can achieve good performance on both cross-domain generalization and fine-tuning accuracy on various benchmarks. In particular, the proposed PCW-Net is designed for two purposes. ...
institutions and the countries involved in structural topology optimization are visually presented through clustering and visual analysis based on CiteSpace. The four metric dimensions of the literatures in this paper are as follows: annual quantity of papers and core countries, core authors and co-aut...
while neglecting the layout and style information that is vital for document image understanding. In this paper, we propose the LayoutLM to jointly model the interaction between text and layout information across scanned document images, which is beneficial for a great number of real-world document ...
I could easily understand the engineering design of the vestibule, once I mapped all the connections on paper. Because the vestibule provides the same output as the sensors we designed in the defense industry, we can now better understand the circuitry that is processing this data. Trust me, ...
To answer this question, we performed the first holistic study of DNN usage in the wild in an attempt to track deployed models and match how these run on widely deployed devices. In our paper, Smart at what cost? Characterising Mobile Deep Neural Networks in the wild [5], accepted at ACM...
machine learning researchers introduced the concept of a vision transformer (ViT) in 2021. This innovative approach serves as an alternative to convolutional neural networks (CNNs) for computer vision applications, as detailed in the paper,An Image Is Worth 16x16 Words: Transformers for Image Recogn...