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

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

Explainable Brain Tumor Classification using CNN and GradCAM

Abstract: One of the most critical neurological conditions is Brain tumors, timely and correct diagnosis is needed for effective treatment. Advances in neuroimaging technology such as MRI, limitations ...
IEEE

Hybrid Integration of CNN and Kolmogorov–Arnold Networks for Multispectral Image Super-Resolution

Abstract: This letter proposes KAN-based multispectral image super-resolution method (KMSR), a novel deep learning framework for multispectral image (MSI) super-resolution (SR) that integrates ...
The Manila Times

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
IEEE

Mamba Cross-Modal Information Fusion Self-Distillation Model for Joint Classification of LiDAR and Hyperspectral Data

Abstract: Recent studies have found that compared to single-modal data, the joint classification of hyperspectral image (HSI) and light detection and ranging (LiDAR) multimodal data can use their ...
IEEE

The ACGAN-AOA-CNN-BiGRU Model for Network Intrusion Detection

Abstract: Addressing the dual challenges of class imbalance and manual hyperparameter tuning in network intrusion detection, this paper proposes a CNN-BiGRU detection model integrating Adversarial ...
IEEE

PixTransNet: A Sensor-Aware CNN–Transformer Model for Magnetic Flux Leakage Defect Segmentation

Abstract: Magnetic flux leakage (MFL) is a widely used nondestructive evaluation technique for pipeline inspection. However, its signals are highly sensitive to noise and geometric distortions, ...
IEEE

Graph Signal Sampling-Based Active Learning for Hyperspectral Image Classification

Abstract: Active learning (AL) has achieved great success in remotely sensed hyperspectral image (HSI) classification due to its ability to select highly informative training samples. An appropriate ...
European Medical Journal

Lightweight Neural Networks Improve Lung Cancer Diagnosis

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
IEEE

Hierarchical Byte-Level Modeling via CNN and Mamba for Encrypted Traffic Classification

Abstract: Encrypted traffic classification, which aims to identify application-layer semantics without decrypting packet pay-loads, has emerged as a pivotal challenge in modern network intelligence ...
IEEE

Enhanced Time-Series Activity Recognition with a Hybrid CNN-SVM Model: Insights from Wearable Sensor Analysis

Abstract: The fundamental requirement of time-series activity detection that uses wearable sensors spreads across healthcare monitoring alongside fitness tracking and smart environments applications.