Deep learning for steganalysis of diverse data types: A review of methods, taxonomy, challenges and future directions

H Kheddar, M Hemis, Y Himeur, D Megías, A Amira - Neurocomputing, 2024 - Elsevier
Steganography and steganalysis are two interrelated aspects of the field of information
security. Steganography seeks to conceal communications, whereas steganalysis aims to …

Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023

M Jafari, D Sadeghi, A Shoeibi, H Alinejad-Rokny… - Applied …, 2024 - Springer
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …

[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 …

I-vit: Integer-only quantization for efficient vision transformer inference

Z Li, Q Gu - Proceedings of the IEEE/CVF International …, 2023 - openaccess.thecvf.com
Abstract Vision Transformers (ViTs) have achieved state-of-the-art performance on various
computer vision applications. However, these models have considerable storage and …

Enhancing intrusion detection: a hybrid machine and deep learning approach

M Sajid, KR Malik, A Almogren, TS Malik… - Journal of Cloud …, 2024 - Springer
The volume of data transferred across communication infrastructures has recently increased
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 …

Improved cocoso method based on frank softmax aggregation operators for t-spherical fuzzy multiple attribute group decision-making

H Wang, T Mahmood, K Ullah - International Journal of Fuzzy Systems, 2023 - Springer
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 …

Softermax: Hardware/software co-design of an efficient softmax for transformers

JR Stevens, R Venkatesan, S Dai… - 2021 58th ACM/IEEE …, 2021 - ieeexplore.ieee.org
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 …

Designing novel AAD pooling in hardware for a convolutional neural network accelerator

K Khalil, O Eldash, A Kumar… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

[HTML][HTML] Towards the development of an explainable e-commerce fake review index: An attribute analytics approach

R Das, W Ahmed, K Sharma, M Hardey… - European Journal of …, 2024 - Elsevier
Instruments of corporate risk and reputation assessment tools are quintessentially
developed on structured quantitative data linked to financial ratios and macroeconomics. An …