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Keyword: BLSTM
Enhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data
The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…
Read More BER Performance Evaluation Using Deep Learning Algorithm for Joint Source Channel Coding in Wireless Networks
In the time past, virtually all the contemporary communication systems depend on distinct source and channel encoding schemes for data transmission. Irrespective of the recorded success of the distinct schemes, the new developed scheme known as joint source channel coding technique has proven to have technically outperformed the conventional schemes. The aim of the study…
Read More Keyword Driven Image Description Generation System
Image description generation is an important area in Computer Vision and Natural Language Processing. This paper introduces a novel architecture for an image description generation system using keywords. The proposed architecture uses a high-level feature such as keywords for generating captions. The important component of caption generation is the deep Bidirectional LSTM network. The space…
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