Detection of fish freshness using artificial intelligence methods
Fish is commonly acknowledged as a highly nutritious food in many regions worldwide, and
humans have been consuming fish for centuries to meet their protein and nutritional …
humans have been consuming fish for centuries to meet their protein and nutritional …
Maize seeds forecasting with hybrid directional and bi‐directional long short‐term memory models
The purity of the seeds is one of the important factors that increase the yield. For this reason,
the classification of maize cultivars constitutes a significant problem. Within the scope of this …
the classification of maize cultivars constitutes a significant problem. Within the scope of this …
[HTML][HTML] Hybridizing Long Short-Term Memory and Bi-Directional Long Short-Term Memory Models for Efficient Classification: A Study on Xanthomonas axonopodis …
This study was conducted on Xanthomonas axonopodis pv, which causes significant
economic losses in the agricultural sector. Here, we study a common bacterial blight disease …
economic losses in the agricultural sector. Here, we study a common bacterial blight disease …
Automated classification of hand-woven and machine-woven carpets based on morphological features using machine learning algorithms
M Isik, B Ozulku, R Kursun, YS Taspinar… - The Journal of The …, 2024 - Taylor & Francis
As a cultural heritage, hand-woven carpets engender trust and admiration in individuals who
recognize their authenticity. It is the expertise of experts who determine whether a carpet is …
recognize their authenticity. It is the expertise of experts who determine whether a carpet is …
Distinguishing between AI images and real images with hybrid image classification methods
YS Taspinar, I Cinar - 2024 13th Mediterranean Conference on …, 2024 - ieeexplore.ieee.org
Due to the rapid proliferation of artificial intelligence applications, some vulnerabilities in
security and ethical issues emerge. With these applications, data such as text, images, audio …
security and ethical issues emerge. With these applications, data such as text, images, audio …
[PDF][PDF] The effectiveness of deep learning methods on groundnut disease detection
Early detection of plant diseases in the agricultural sector is considered an important goal to
increase productivity and minimize damage. This study deals with the use of deep learning …
increase productivity and minimize damage. This study deals with the use of deep learning …
A comparative analysis of machine learning algorithms for waste classification: inceptionv3 and chi-square features
Effective waste management requires the correct categorization of recyclables. It is possible
to classify organic waste and recyclable waste using machine learning techniques …
to classify organic waste and recyclable waste using machine learning techniques …
Detecting Industrial Potato Chips Defects with Machine Learning Methods Using Deep Features
G Taspinar, M Koklu - Intelligent Methods In Engineering Sciences, 2024 - imiens.org
Detection of production defects in industrial foods is vital to protect consumer health. Early
detection of these errors can minimize the economic losses of manufacturers by reducing …
detection of these errors can minimize the economic losses of manufacturers by reducing …
Deep Learning-Based Classification of Skin Lesion Dermoscopic Images for Melanoma Diagnosis
This study examined the effectiveness of artificial intelligence and machine learning
methods in accurately categorizing skin cancers. We used the ISIC 2019 Skin Lesion …
methods in accurately categorizing skin cancers. We used the ISIC 2019 Skin Lesion …
[PDF][PDF] Classification of organic and recyclable waste based on feature extraction and machine learning algorithms
Managing solid waste effectively requires the proper classification of waste. To determine
whether a waste is organic or recyclable, machine learning methods can be used. This study …
whether a waste is organic or recyclable, machine learning methods can be used. This study …