IEEE

Deep Learning-Based Mushroom Species Classification: Analyzing the Performance of CNN on Diverse Fungi

Abstract: This paper proposes the classification of mushrooms using the EfficientNetB7 deep learning architecture. Correct classification of mushrooms is important because most species are considered ...
IEEE

Hybrid Deep Learning for Portable Weather Forecasting: Real-Time Predictions Using CNN-LSTM-Transformer Models

Abstract: Accurate weather forecasting is critical for agriculture, disaster management, and transportation sectors. However, traditional forecasting systems often require extensive computational ...
IEEE

An Interpretable Machine Learning Model for Leukemia Diagnosis Using CNN-SVM and Explainable AI

Abstract: The method uses a new approach for classifying leukaemia by connecting a CNN with an SVM classifier built especially for the task. Because white blood cell morphology diagnosis is crucial ...
IEEE

Transfer Learning-Enhanced CNN-LSTM Model for Banana Plant Disease Detection

Abstract: Bananas are one of the widely cultivated and eaten fruits globally, playing a effective role in the agricultural economy of many regions, including tropical and subtropical regions. However, ...
IEEE

Learning to Count Targets from Dual-Window: A CNN Approach for OFDM ISAC

Abstract: Integrated Sensing and Communication (ISAC) with Orthogonal Frequency Division Multiplexing (OFDM) waveforms is a key enabler for next-generation wireless systems. Recent studies show that ...
IEEE

Automated Deep Learning System for Early Detection of Stroke Using CNN Architecture

Abstract: Strokes are a major cause of disability worldwide, with ischemic and hemorrhagic strokes accounting for the majority of cases. In India, stroke remains the second most common cause of ...
IEEE

Leveraging CNN-RF Models for Enhanced Serve Shot Strategies in Table Tennis

Abstract: The definition of which serve strokes to use depends on the technique practiced and the specific tactical conditions during the game because of the strategic complexity inherent in serve ...
IEEE

Predictive Autism Analysis: Integrating CNN and RNN with Ensemble Learning

Abstract: Timely identification of Autism Spectrum Disorder (ASD) is essential for successful intervention, but current diagnostic methods often depend on subjective observations, potentially missing ...
IEEE

Deep Learning for Aerial and Satellite Image Analysis: a CNN-Based Approach

Abstract: Applications like disaster management, urban planning, and environmental monitoring rely on satellite image categorization. This project develops a machine learning pipeline using ...
IEEE

How Does the Machine Perceive Depth for Indoor Single Images with CNN?

Abstract: Depth estimation from a single image is a challenging problem in computer vision because binocular disparity or motion information is not available in the given input. Whereas impressive ...
IEEE

Deploying Deep Learning for Real-Time Tsunami Monitoring: A CNN-LSTM Model for Sensor-Based Prediction

Abstract: Early detection of tsunamis is essential for disaster risk reduction and minimizing loss of life. This research introduces an advanced deep learning-based tsunami detection model that ...
IEEE

Acoustic Traffic Attribute Classification for ITS: A Comparative Study of Machine Learning and CNN Approaches

Abstract: Reliable information about traffic attributes, including vehicle type, speed range, and direction, is essential for traffic management and intelligent transportation systems (ITS). Although ...