IEEE

Olfactory Prediction Using CNN-CBAM Model

Abstract: Olfactory perception prediction plays a vital role in multi-modal sensory research, offering insights for health monitoring and personalized experiences. In this work, we propose a novel CNN ...
IEEE

Short-Term Photovoltaic Power Prediction Based on GWO-CNN-LSTM-MATT Hybrid Model

Abstract: This paper proposes a photovoltaic power prediction model based on GWO-CNN-LSTM-MATT. Firstly, the convolutional neural network (CNN) is used to extract the spatial features and local ...
IEEE

GAF-CNN-LSTM Hybrid Model for Power Load Forecasting in Non-Stationary Grids

Abstract: With the increasing penetration of renewable energy in power systems, load forecasting faces dual challenges of modeling non-stationary fluctuations and spatiotemporally coupled features.
IEEE

Enabling Decoder-only Language Model Inference on a CNN Accelerator

Abstract: The remarkable success of Transformer architectures in Natural Language Processing (NLP) has led to increased demand for embedded systems capable of efficiently handling NLP tasks along with ...
IEEE

Enhancing Intrusion Detection in Cloud Computing Environments Using a Hybrid BiGRU-CNN Model

Abstract: Due to its adaptability and pay-as-you-go pricing model, cloud computing has quickly become the go-to option for all types of IT companies. The majority of cloud intrusion detection systems ...
IEEE

A Traffic Flow Prediction Model Based on Vehicle Travel Big Data and Simulation

Abstract: With the accelerating global urbanization process, urban transportation systems are facing multiple challenges, including surging traffic flow, environmental protection, and road safety. To ...
IEEE

Efficient Infrared Small Target Detection via Fixed-Rank Representation and Patch-Tensor Model

Abstract: Robust and efficient detection of infrared small targets is the key technology of the infrared search and tracking (IRST) system. Low-rank sparse decomposition (LRSD) is a powerful tool for ...