Results 91 to 100 of about 5,255 (193)

Pollen Grain Classification Using Some Convolutional Neural Network Architectures

Journal of Imaging
The main objective of this work is to use convolutional neural networks (CNN) to improve the performance in previous works on their baseline for pollen grain classification, by improving the performance of the following eight popular architectures ...
Benjamin Garga, Hamadjam Abboubakar, Rodrigue Saoungoumi Sourpele, David Libouga Li Gwet, Laurent Bitjoka   +4 more
doaj   +1 more source

Deep learning algorithms for detecting fractured instruments in root canals

BMC Oral Health
Background Identifying fractured endodontic instruments (FEIs) in periapical radiographs (PAs) is a critical yet challenging aspect of root canal treatment (RCT) due to anatomical complexities and overlapping structures.
Ekin Deniz Çatmabacak, İrem Çetinkaya
doaj   +1 more source

Severity Classification of Conjunctival Hyperaemia by Deep Neural Network Ensembles

Journal of Ophthalmology, 2019
Conjunctival hyperaemia is a common clinical ophthalmological finding and can be a symptom of various ocular disorders. Although several severity classification criteria have been proposed, none include objective severity criteria.
Hiroki Masumoto, Hitoshi Tabuchi, Tsuyoshi Yoneda, Shunsuke Nakakura, Hideharu Ohsugi, Tamaki Sumi, Atsuki Fukushima   +6 more
doaj   +1 more source

Apple Varieties Classification Using Deep Features and Machine Learning

Agriculture
Having the advantages of speed, suitability and high accuracy, computer vision has been effectively utilized as a non-destructive approach to automatically recognize and classify fruits and vegetables, to meet the increased demand for food quality ...
Alper Taner, Mahtem Teweldemedhin Mengstu, Kemal Çağatay Selvi, Hüseyin Duran, İbrahim Gür, Nicoleta Ungureanu   +5 more
doaj   +1 more source

A Real-Time Anomaly Detection System for Video Surveillance Using DenseNet201

International Journal of Innovative Research in Information Security
Surveillance systems are pivotal for public safety; yet real-time anomaly detection remains a challenging task. Traditional systems rely on human monitoring, which is inefficient for large-scale deployments. This study addresses the critical rational for automated deviationsdetection by developing a system capable of identifying abnormal events in ...
Suma S, Islapuram Lokesh
openaire   +1 more source

Improving Pinworm Eggs Segmentation With Stacked Transfer Learning-Based U-Net Ensembles

IEEE Access
Human parasites negatively impact health and reduce the quality of life worldwide. Therefore, preventing the spread of parasites and treating infections are essential for public health.
Emre Ozbilge, Mehmet Karlitas, Emrah Guler, Ebru Ozbilge, Huseyin Kaya Suer   +4 more
doaj   +1 more source

Detection and Mitigation of Deepfake Attacks in Cybersecurity : Leveraging Computer Vision and Deep Learning [PDF]

In recent years, the production of fake content has grown exponentially, challenging cybersecurity, digital integrity, and public trust. The thesis presented here attempts to implement and evaluate a deepfake detection system that uses computer vision ...
Zare Janakbari, Poorya
core  

Hybrid Feature Extraction Technique-based Alzheimer’s Disease Detection Model Using MRI Images

Journal of Disability Research
Detecting Alzheimer’s disease (AD) using magnetic resonance imaging (MRI) is essential for early diagnosis and management. This study introduces a new method for detecting AD by combining three robust models: DenseNet201, EfficientNet B7, and extremely ...
Hazim Saleh Al-Rawashdeh, Aminu Usman, Ashit Kumar Dutta, Abdul Rahaman Wahab Sait, Hazim AlRawashdeh   +4 more
doaj   +1 more source

Fruit Grade Classification and Disease Detection using Deep Learning Techniques [PDF]

Ensuring optimal food quality and agricultural productivity hinges on effective fruit quality assessment and disease detection. Introducing a comprehensive strategy employing deep learning techniques to address critical aspects of fruit quality ...
K. Gokul Prasath, R. Lakshman Vignesh, S. Mary Praveena, R. Aakash,
core   +1 more source

A Comparative Evaluation of CNN and Transfer Learning Models for Multi-Class Skin Disease Classification

Engineering Proceedings
The automated classification of skin diseases has the potential to significantly enhance patient outcomes through early and targeted treatment.
Ivana Lucia Kharisma, Rifki Arief Munandar, D Ihsan Maulana, Mochamad Naufal Rizky, Kamdan   +4 more
doaj   +1 more source