Deep learning for steganalysis of diverse data types: A review of methods, taxonomy, challenges and future directions
Steganography and steganalysis are two interrelated aspects of the field of information
security. Steganography seeks to conceal communications, whereas steganalysis aims to …
security. Steganography seeks to conceal communications, whereas steganalysis aims to …
[HTML][HTML] A deep learning technique for intrusion detection system using a Recurrent Neural Networks based framework
SM Kasongo - Computer Communications, 2023 - Elsevier
In recent years, the spike in the amount of information transmitted through communication
infrastructures has increased due to the advances in technologies such as cloud computing …
infrastructures has increased due to the advances in technologies such as cloud computing …
Memristive dynamics enabled neuromorphic computing systems
The slowing down of transistor scaling and explosive growth for intelligence computing
power emerge as the two driving factors for the study of novel devices and materials to …
power emerge as the two driving factors for the study of novel devices and materials to …
I-vit: Integer-only quantization for efficient vision transformer inference
Abstract Vision Transformers (ViTs) have achieved state-of-the-art performance on various
computer vision applications. However, these models have considerable storage and …
computer vision applications. However, these models have considerable storage and …
Enhancing intrusion detection: a hybrid machine and deep learning approach
The volume of data transferred across communication infrastructures has recently increased
due to technological advancements in cloud computing, the Internet of Things (IoT), and …
due to technological advancements in cloud computing, the Internet of Things (IoT), and …
Emotion recognition based on brain-like multimodal hierarchical perception
X Zhu, Y Huang, X Wang, R Wang - Multimedia Tools and Applications, 2024 - Springer
Emotion recognition has gained prominence in diverse applications ranging from safe
driving and e-commerce to healthcare. Traditional approaches have often relied on single …
driving and e-commerce to healthcare. Traditional approaches have often relied on single …
Improved CoCoSo method based on Frank softmax aggregation operators for T-spherical fuzzy multiple attribute group decision-making
In this article, a novel CoCoSo (Combined compromise solution) method based on Frank
operational laws and softmax function is investigated to handle multiple attribute group …
operational laws and softmax function is investigated to handle multiple attribute group …
Designing novel AAD pooling in hardware for a convolutional neural network accelerator
Convolutional neural network (CNN) hardware accelerators for specialized Internet of
Things (IoT) requiring high accuracy is an emerging research topic. The pooling module in a …
Things (IoT) requiring high accuracy is an emerging research topic. The pooling module in a …
Softermax: Hardware/software co-design of an efficient softmax for transformers
Transformers have transformed the field of natural language processing. Their superior
performance is largely attributed to the use of stacked “self-attention” layers, each of which …
performance is largely attributed to the use of stacked “self-attention” layers, each of which …
Sima: Simple softmax-free attention for vision transformers
Recently, vision transformers have become very popular. However, deploying them in many
applications is computationally expensive partly due to the Softmax layer in the attention …
applications is computationally expensive partly due to the Softmax layer in the attention …