Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach

MS Islam, MN Kabir, NA Ghani, KZ Zamli… - Artificial Intelligence …, 2024 - Springer
Social media is used to categorise products or services, but analysing vast comments is time-
consuming. Researchers use sentiment analysis via natural language processing …

EMSN: An energy-efficient memristive sequencer network for human emotion classification in mental health monitoring

X Ji, Z Dong, Y Han, CS Lai, G Zhou… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Mental health problems are an increasingly common social issue severely affecting health
and well-being. Multimedia processing technologies via facial expression show appealing …

Advancements in affective disorder detection: Using multimodal physiological signals and neuromorphic computing based on snns

F Tian, L Zhang, L Zhu, M Zhao, J Liu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Currently, the integration of artificial intelligence (AI) techniques with multimodal
physiological signals represents a pivotal approach to detect affective disorders (ADs). With …

ICNCS: internal cascaded neuromorphic computing system for fast electric vehicle state of charge estimation

Z Dong, X Ji, J Wang, Y Gu, J Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accuracy and speed of Lithium-ion battery state of charge (SOC) estimation determine the
reliability and stability of electric vehicle (EV), as well as promoting the development of smart …

A storage-efficient SNN–CNN hybrid network with RRAM-implemented weights for traffic signs recognition

Y Zhang, H Xu, L Huang, C Chen - Engineering Applications of Artificial …, 2023 - Elsevier
Abstract Traffic Signs Recognition (TSR) is a key technology to implement Automatic Driving
System (ADS) and Advanced Driver Assistant System (ADAS). Numerous efforts have been …

High-performance and energy-efficient leaky integrate-and-fire neuron and spike timing-dependent plasticity circuits in 7nm FinFET technology

MKQ Jooq, MR Azghadi, F Behbahani… - IEEE …, 2023 - ieeexplore.ieee.org
In designing neuromorphic circuits and systems, developing compact and energy-efficient
neuron and synapse circuits is essential for high-performance on-chip neural architectures …

A hybrid method for state-of-charge estimation for lithium-ion batteries using a long short-term memory network combined with attention and a Kalman filter

X Zhang, Y Huang, Z Zhang, H Lin, Y Zeng, M Gao - Energies, 2022 - mdpi.com
A battery management system (BMS) is an important link between on-board power battery
and electric vehicles. The BMS is used to collect, process, and store important information …

Bioinspired memristive neural network circuit design of cross-modal associative memory

J Liu, F Xiong, Y Zhou, S Duan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The development of brain-like artificial intelligence is based on the cognitive functions of the
brain, which are influenced by the cross-modal interactions of learning and memory …

DECNet: A Non-Contacting Dual-Modality Emotion Classification Network for Driver Health Monitoring

Z Dong, C Hu, S Zhou, L Zhu, J Wang… - Proceedings of the …, 2024 - openaccess.thecvf.com
Negative emotions have been identified as significant factors influencing driver behavior,
easily leading to extremely serious traffic accidents. Hence, there is a pressing need to …

MDGN: Circuit design of memristor‐based denoising autoencoder and gated recurrent unit network for lithium‐ion battery state of charge estimation

J Wang, X Zhang, Y Han, CS Lai… - IET Renewable …, 2024 - Wiley Online Library
Due to the highly complex and non‐linear physical dynamics of lithium‐ion batteries, it is
unfeasible to measure the state of charge (SOC) directly. Designing systems capable of …