IEEE

Deep Learning for Handwritten Hindi Character Recognition: A CNN-Based Implementation

Abstract: This manuscript delineates a sophisticated framework for the recognition of handwritten Hindi characters, employing diverse deep learning methodologies. Within this study, we proffer a ...
IEEE

SDCnet: A Deep Learning Network Model for Road Segmentation Based on CNN and Transformer

Abstract: Road segmentation is a key task in remote sensing semantic segmentation, and the existing deep learning methods still have the problems of insufficient fineness, difficulty in modeling ...
IEEE

A Novel Transformer-CNN Hybrid Deep Learning Architecture for Robust Broad-Coverage Diagnosis of Eye Diseases on Color Fundus Images

Abstract: We present a novel and robust deep-learning architecture that takes into account the pathological characteristics of eye diseases on color fundus images. The proposed hybrid architecture is ...
IEEE

Deep Learning for Channel Code Type Recognition

Abstract: Channel code type recognition is critical for enabling receivers to discern codes without prior knowledge. Despite the promise of deep learning approaches in this field, they often encounter ...
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We drilled deep under the sea to learn more about mega-earthquakes and tsunamis

Far beneath the waves, down in the depths of the Japan Trench—seven kilometers below sea level—lie hidden clues about some of the most powerful earthquakes and tsunamis on Earth. Subscribe to our ...
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 in Radiology: A Comparative Study of CNN Architectures for Automated Detection of Bone Fractures

Abstract: The research introduces an automatic bone fracture detection method through deep learning networks which evaluates three CNN architectures including Custom CNN and MobileNetV2 and ResNet50.
IEEE

Enhanced Eye Disease Detection with YOLOv10 and Convolutional Neural Networks (CNN) in Deep Learning

Abstract: In this study, we present an eye disease detection and prevention solution based on deep learning techniques, CNN and YOLOv10. The main objective of this system is to detect multiple ...