Results 201 to 210 of about 16,939 (236)
Bidirectional LSTM Models for DGA Classification
Communications in Computer and Information Science, 2019 The paper describes our submission to the shared task on DGA classification at DMD 2018. The approach is based on a Deep Learning architecture using bidirectional LSTM neural networks. Similar models are used in both the tasks, the first one is to identify the DGA generated domain name and the second one is to detect and categorize the DGA generated ...
Giuseppe Attardi, Attardi Giuseppe
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Enhancing Electrical Load Prediction Using a Bidirectional LSTM Neural Network
Electronics (Switzerland), 2023 Precise anticipation of electrical demand holds crucial importance for the optimal operation of power systems and the effective management of energy markets within the domain of energy planning.
Christos Pavlatos +2 more
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Car Tourist Trajectory Prediction Based on Bidirectional LSTM Neural Network
Electronics (Switzerland), 2021 COVID-19 has greatly affected the tourist industry and ways of travel. According to the UNTWO predictions, the number of international tourist arrivals will be slowly growing by the end of 2021.
Sergei Mikhailov +2 more
exaly +2 more sources
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Bidirectional LSTM with Extended Input Context
2018 11th International Symposium on Chinese Spoken Language Processing (ISCSLP), 2018Long short-term memory (LSTM) unit has been widely used in speech recognition tasks, both for acoustic model and language model. For offline speech recognition task, bidirectional LSTM (BLSTM) is the state-of-the-art acoustic model. In this paper, we propose the BLSTM with extended input context (BLSTM-E), which achieves higher speech recognition ...
Gaofeng Cheng +3 more
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Attention augmentation with multi-residual in bidirectional LSTM
Neurocomputing, 2020Abstract Recurrent neural networks (RNNs) have been proven to be efficient in processing sequential data. However, the traditional RNNs have suffered from the gradient diminishing problem until the advent of Long Short-Term Memory (LSTM). However, LSTM is weak in capturing long-time dependency in sequential data due to the inadequacy of memory ...
Ye Wang 0006 +4 more
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Anomaly Detection Using Bidirectional LSTM
2020This paper presents an anomaly detection approach based on deep learning techniques. A bidirectional long-short-term memory (Bi-LSTM) was applied on the UNSW-NB15 dataset to detect the anomalies. UNSW-NB15 represents raw network packets that contains both the normal activities and anomalies.
Sarah Aljbali, Kaushik Roy
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Indoor Localization Using Bidirectional LSTM Networks
2021 13th International Conference on Advanced Computational Intelligence (ICACI), 2021Indoor localization witnessed the flourishing development in location based service for indoor environments. Regarding the availability of access points (AP) and its low cost for industry popularization, one of promising tool for localization is based on WiFi fingerprints.
Dong Pang, Xinyi Le
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A bidirectional LSTM deep learning approach for intrusion detection
Expert Systems With Applications, 2021Abstract The rise in computer networks and internet attacks has become alarming for most service providers. It has triggered the need for the development and implementation of intrusion detection systems (IDSs) to help prevent and or mitigate the challenges posed by network intruders.
Imrana Yakubu +2 more
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Bidirectional LSTM for Author Gender Identification
2018Author profiling consists in inferring the authors’ gender, age, native language, dialects or personality by examining his/her written text. This important task is a very active research area because of its utility in crime, marketing and business.
Bassem Bsir, Mounir Zrigui
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Describing Video With Attention-Based Bidirectional LSTM
IEEE Transactions on Cybernetics, 2019Video captioning has been attracting broad research attention in the multimedia community. However, most existing approaches heavily rely on static visual information or partially capture the local temporal knowledge (e.g., within 16 frames), thus hardly describing motions accurately from a global view.
Yi Bin +5 more
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