IEEE

Crispvision: Apple Leaf Disease Detection Using Machine Learning and Deeper CNN

Abstract: Identifying diseases in apple leaves plays a vital role in boosting farm productivity and preventing crop losses. This research introduces a comprehensive approach for classifying images of ...
IEEE

Enhancing Medical Image Super-Resolution Using CNN and GAN Approaches

Abstract: Improving the resolution of medical images is an important task in ensuring trustworthy diagnosis and effective monitoring of diseases. Of the newest deep learning algorithms, Convolutional ...
IEEE

A Verified Synergistic Deep Learning Framework for Copyrighted Character Recognition Using CNN and Transformer Integration

Abstract: In this paper, we proposed a novel deep learning framework, the Synergistic Deep Learning Model, for recognizing copyrighted characters with heightened accuracy and minimized overfitting.
IEEE

A Survey of Deep Learning-Based Human Pose Estimation: Methods, Datasets, and Evaluation Metrics

Abstract: Human pose estimation has emerged as one of the most prominent research directions in computer vision in recent years. This technology aims to acquire human pose information from images or ...
IEEE

MSSEAG-UNet: A Novel Deep Learning Architecture for Cloud Segmentation in Fisheye Sky Images and Solar Energy Forecast

Abstract: This study analyzes sky images captured using a ground-based fisheye camera, aiming to address the challenge of accurately segmenting clouds, which is difficult due to their fuzzy and ...
IEEE

Deep Learning Approaches to Babylonian Numeral Recognition: A CNN-SVM Hybrid Model

Abstract: This paper presents a novel deep learning framework for classifying Babylonian numerals by integrating Convolutional Neural Networks (CNNs) with a hybrid CNN-SVM model. The core ...
IEEE

Deep Learning-Based Hyperparameter Optimization for Enhanced Segmentation of RGB Images in Oil Spill Detection Within Port Environments

Abstract: Accurate detection of oil spills in dynamic port environments remains critical for timely response and effective environmental protection. Recent studies have explored the application of ...