DRAFT 发表于 2025-3-26 21:08:43
Aufzeichnung von Fernsehprogrammen,mage recognition field due to the discriminative power of Convolutional Neural Network (CNN). In this paper, we first propose a novel Multi-Region Ensemble CNN (MRE-CNN) framework for facial expression recognition, which aims to enhance the learning power of CNN models by capturing both the global aanniversary 发表于 2025-3-27 03:00:10
http://reply.papertrans.cn/17/1627/162642/162642_32.png首创精神 发表于 2025-3-27 07:08:03
W. Burkhardtsmaier,W. Buschbeckhave been developed to discover new DTIs, whereas the prediction accuracy is not very satisfactory. Most existing computational methods are based on homogeneous networks or on integrating multiple data sources, without considering the feature associations between gene and drug data. In this paper, wCardiac-Output 发表于 2025-3-27 12:43:25
,Fernsehübertragungen auf Leitungen,n this paper, we propose a hierarchical Convolution Neural Network (Hier-CNN) for emotion cause detection. Our Hier-CNN model deals with the feature sparse problem through a clause-level encoder, and handles the less event-based information problem by a subtweet-level encoder. In the clause-level enFEAT 发表于 2025-3-27 14:57:42
https://doi.org/10.1007/978-3-642-79349-3ervation noise, which is dynamic in our marine virtual sensor task. Typically, dynamic noise is not trained directly, but approximated through terms in the loss function. Unfortunately, this noise loss function needs to be scaled by a trade-off-parameter to achieve accurate uncertainties. In this paobnoxious 发表于 2025-3-27 17:47:45
https://doi.org/10.1007/978-3-642-79349-3hey have been shown to work successfully in supervised classification and regression tasks, as well as in training unsupervised autoencoders. This work has two contributions: First, we show that dropout and dropconnect on input units, previously proposed for deep multi-layer neural networks, can als无关紧要 发表于 2025-3-28 00:06:55
https://doi.org/10.1007/978-3-642-79349-3ed models in machine translation, which the models can automatically search for parts of a sentence that are relevant to a target word, we propose a multi-level attention model with maximum matching matrix rank to simulate what human does when finding a good answer for a query question. Firstly, weSedative 发表于 2025-3-28 04:53:44
http://reply.papertrans.cn/17/1627/162642/162642_38.pngencomiast 发表于 2025-3-28 08:44:14
http://reply.papertrans.cn/17/1627/162642/162642_39.png行为 发表于 2025-3-28 12:47:01
Thorsten Quandt,Jürgen Wilke,Thilo Papege text. While the state-of-the-art for this task has rapidly improved in terms of n-gram metrics, these models tend to output the same generic captions for similar images. In this work, we address this limitation and train a model that generates more diverse and specific captions through an unsuper