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Ulzhan Bissarinova, Aidana Tleuken, Sofiya Alimukhambetova, Huseyin Atakan Varol and Ferhat Karaca
This paper introduces a deep learning (DL) tool capable of classifying cities and revealing the features that characterize each city from a visual perspective. The study utilizes city view data captured from satellites and employs a methodology involving...
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Efrain Noa-Yarasca, Javier M. Osorio Leyton and Jay P. Angerer
Timely forecasting of aboveground vegetation biomass is crucial for effective management and ensuring food security. However, research on predicting aboveground biomass remains scarce. Artificial intelligence (AI) methods could bridge this research gap a...
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Dania Tamayo-Vera, Xiuquan Wang and Morteza Mesbah
The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic domain is pivotal for addressing the multifaceted challenges posed by climate change on agriculture. This paper embarks on a systematic review to dissect the current ut...
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Utpal Barman, Parismita Sarma, Mirzanur Rahman, Vaskar Deka, Swati Lahkar, Vaishali Sharma and Manob Jyoti Saikia
Invading pests and diseases always degrade the quality and quantity of plants. Early and accurate identification of plant diseases is critical for plant health and growth. This work proposes a smartphone-based solution using a Vision Transformer (ViT) mo...
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Zahra Ameli, Shabnam Jafarpoor Nesheli and Eric N. Landis
The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application ...
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Shiplu Das, Sanjoy Pratihar, Buddhadeb Pradhan, Rutvij H. Jhaveri and Francesco Benedetto
The main purpose of a detection system is to ascertain the state of an individual?s eyes, whether they are open and alert or closed, and then alert them to their level of fatigue. As a result of this, they will refrain from approaching an accident site. ...
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Gulsum Alicioglu and Bo Sun
Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sensitiv...
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Nawaf Alharbi, Mustafa Youldash, Duha Alotaibi, Haya Aldossary, Reema Albrahim, Reham Alzahrani, Wahbia Ahmed Saleh, Sunday O. Olatunji and May Issa Aldossary
Fetal hypoxia is a condition characterized by a lack of oxygen supply in a developing fetus in the womb. It can cause potential risks, leading to abnormalities, birth defects, and even mortality. Cardiotocograph (CTG) monitoring is among the techniques t...
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Salman Ibne Eunus, Shahriar Hossain, A. E. M. Ridwan, Ashik Adnan, Md. Saiful Islam, Dewan Ziaul Karim, Golam Rabiul Alam and Jia Uddin
Accidents due to defective railway lines and derailments are common disasters that are observed frequently in Southeast Asian countries. It is imperative to run proper diagnosis over the detection of such faults to prevent such accidents. However, manual...
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Wandile Nhlapho, Marcellin Atemkeng, Yusuf Brima and Jean-Claude Ndogmo
The advent of deep learning (DL) has revolutionized medical imaging, offering unprecedented avenues for accurate disease classification and diagnosis. DL models have shown remarkable promise for classifying brain tumors from Magnetic Resonance Imaging (M...
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