Ishak Pacal

Ishak Pacal
Iğdır Üniversitesi · Department of Computer Engineering

PhD
Open to academic collaboration.

About

50
Publications
14,375
Reads
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1,047
Citations

Publications

Publications (50)
Article
Full-text available
Skin cancer represents a significant global health concern, where early and precise diagnosis plays a pivotal role in improving treatment efficacy and patient survival rates. Nonetheless, the inherent visual similarities between benign and malignant lesions pose substantial challenges to accurate classification. To overcome these obstacles, this st...
Article
Agriculture forms the cornerstone of global food security, with olives playing a pivotal role not only as a food source but also in cosmetics, medicine, and other industries. However, diseases affecting olive trees pose significant threats to agricultural productivity and economic stability, underscoring the need for innovative detection solutions....
Article
Full-text available
Background: Cervical cancer is a leading health concern for women globally, necessitating accurate and timely diagnostic methods. While the Papanicolaou smear (Pap smear) test remains the gold standard for cervical cancer screening, it is time-consuming and prone to human error. This highlights the need for automated diagnostic tools to improve eff...
Article
Full-text available
This study investigates the optimization of bioactive components in thermosonicated black carrot juice using response surface methodology (RSM) and gradient boosting (GB) modeling techniques. Thermosonication, a combination of ultrasound and heat, was applied to enhance the nutritional quality of black carrot juice, which is rich in anthocyanins, p...
Article
Full-text available
Lung cancer is the most common cause of cancer-related mortality globally. Early diagnosis of this highly fatal and prevalent disease can significantly improve survival rates and prevent its progression. Computed tomography (CT) is the gold standard imaging modality for lung cancer diagnosis, offering critical insights into the assessment of lung n...
Article
Full-text available
Corn is not only widely used in industry but also a crucial staple food. Early detection of corn leaf diseases is vital to prevent crop loss. Farmers and agricultural engineers often rely on computer-aided systems for early diagnosis of plant diseases. Among the various methods, deep learning stands out as the most popular and effective approach fo...
Conference Paper
Full-text available
The early detection of cracks is crucial for ensuring the safety and durability of concrete structures, as these cracks can lead to significant structural damage if not addressed promptly. In this context, the rapid and accurate identification of cracks plays a vital role in enhancing the effectiveness of structural damage assessments. This study e...
Article
This study investigates the effectiveness of deep learning models in diagnosing cardiac amyloidosis using 99mTc-PYP scintigraphy. We evaluated more than 40 deep learning models, including both convolutional neural networks (CNNs) and Vision Transformer (ViT) models. The highest-performing model achieved 89.80% accuracy. The study highlights the pot...
Conference Paper
Full-text available
Alzheimer's disease is a progressive neurodegenerative disorder associated with the loss of brain cells as people age, affecting millions globally. Early diagnosis is crucial for improving patients' quality of life, optimizing treatment, and reducing the burden on healthcare systems. In recent years, deep learning algorithms have made significant a...
Article
Full-text available
Agriculture is one of the most crucial sectors, meeting the fundamental food needs of humanity. Plant diseases increase food economic and food security concerns for countries and disrupt their agricultural planning. Traditional methods for detecting plant diseases require a lot of labor and time. Consequently, many researchers and institutions stri...
Conference Paper
Full-text available
The early detection of cracks is crucial for ensuring the safety and durability of concrete structures, as these cracks can lead to significant structural damage if not addressed promptly. In this context, the rapid and accurate identification of cracks plays a vital role in enhancing the effectiveness of structural damage assessments. This study e...
Conference Paper
Full-text available
In this study, we propose a novel deep learning model, SE-Xception, which integrates Squeeze-and-Excitation (SE) blocks into the Xception architecture for solid waste classification. This model is designed to address the growing global challenge of waste accumulation by enhancing the classification accuracy of waste materials. Utilizing a publicly...
Article
Full-text available
Sugarcane is a crucial agricultural crop, providing 75% of the world's sugar production. Like all plant species, any disease that affects sugarcane can significantly impact yield and planning. Traditional manual methods for diagnosing diseases in sugarcane leaves are slow, inefficient, and often lack accuracy. In this study, we present a deep learn...
Article
Full-text available
Breast cancer is one of the most prevalent forms of cancer among women, and early diagnosis is of vital importance. In recent years, machine learning algorithms have demonstrated high accuracy in breast cancer detection, contributing to earlier diagnoses. Various machine learning models can analyze tumor characteristics and assist in cancer identif...
Conference Paper
Full-text available
Potatoes rank among the most important staple foods in the world, forming part of the core diet for about 1.5 billion people. Non-cereal agricultural products rank them among the best. However, diseases like late blight and early blight cause severe yield and storability losses. Early detection of such diseases would be of the essence to mitigate t...
Article
Full-text available
Sugar cane is an important agricultural product that provides 75% of the world's sugar production. As with all plant species, any disease affecting sugarcane can significantly impact yields and planning. Diagnosing diseases in sugarcane leaves using traditional methods is slow, inefficient, and often lacking in accuracy. This study presents a deep...
Article
Full-text available
Skin cancer is one of the most frequently occurring cancers worldwide, and early detection is crucial for effective treatment. Dermatologists often face challenges such as heavy data demands, potential human errors, and strict time limits, which can negatively affect diagnostic outcomes. Deep learning–based diagnostic systems offer quick, accurate...
Article
Full-text available
The early and accurate diagnosis of brain tumors is critical for effective treatment planning, with Magnetic Resonance Imaging (MRI) serving as a key tool in the non-invasive examination of such conditions. Despite the advancements in Computer-Aided Diagnosis (CADx) systems powered by deep learning, the challenge of accurately classifying brain tum...
Article
Full-text available
Lung infections, such as pneumonia, bronchitis, tuberculosis, and notably COVID-19 caused by the SARS-CoV-2 virus, have caused widespread devastation globally, resulting in a significant loss of life. Timely and precise diagnosis of these respiratory diseases is crucial in controlling their spread and reducing their deadly impact. However, diagnost...
Article
Full-text available
Medical datasets often have a skewed class distribution and a lack of high-quality annotated images. However, deep learning methods require a large amount of labeled data for classification. In this study, we present a few-shot learning approach for the classification of ultrasound breast cancer images using meta-learning methods. We used prototypi...
Article
This study aims to provide an effective solution for the autonomous identification of dental implant brands through a deep learning-based computer diagnostic system. It also seeks to ascertain the system’s potential in clinical practices and to offer a strategic framework for improving diagnosis and treatment processes in implantology. This study e...
Article
Full-text available
Plant diseases cause significant agricultural losses, demanding accurate detection methods. Traditional approaches relying on expert knowledge may be biased, but advancements in computing, particularly deep learning, offer non-experts effective tools. This study focuses on fine-tuning cutting-edge pre-trained CNN and vision transformer models to cl...
Conference Paper
Full-text available
Lung cancer poses a challenging global health issue, necessitating early diagnosis to enhance treatment effectiveness and patient prognosis. This study investigates the utilization of deep learning methodologies, with a specific focus on the Swin Transformer architecture, to automate the detection of lung cancer from computed tomography (CT) scans....
Article
Full-text available
Serious consequences due to brain tumors necessitate a timely and accurate diagnosis. However, obstacles such as suboptimal imaging quality, issues with data integrity, varying tumor types and stages, and potential errors in interpretation hinder the achievement of precise and prompt diagnoses. The rapid identification of brain tumors plays a pivot...
Article
In cases where the brands of implants are not known, treatment options can be significantly limited in potential complications arising from implant procedures. This research aims to explore the application of deep learning techniques for the classification of dental implant systems using panoramic radiographs. The primary objective is to assess the...
Article
Full-text available
This study focuses on real-time hand gesture recognition in the Turkish sign language detection system. YOLOv4-CSP based on convolutional neural network (CNN), a state-of-the-art object detection algorithm, is used to provide real-time and high-performance detection. The YOLOv4-CSP algorithm is created by adding CSPNet to the neck of the original Y...
Article
Full-text available
Deep learning integration in cancer diagnosis enhances accuracy and diagnosis speed which helps clinical decision-making and improves health outcomes. Despite all these benefits in cancer diagnosis, the present AI models in urology cancer diagnosis have not been sufficiently reviewed systematically. This paper reviews the artificial intelligence ap...
Article
Full-text available
Effective image and video annotation is a fundamental pillar in computer vision and artificial intelligence, crucial for the development of accurate machine learning models. Object tracking and image retrieval techniques are essential in this process, significantly improving the efficiency and accuracy of automatic annotation. This paper systematic...
Preprint
Full-text available
Plant diseases are a major factor contributing to agricultural production losses, necessitating effective disease detection and classification methods. Traditional manual approaches heavily rely on expert knowledge, which can introduce biases. However, advancements in computing and image processing have opened up possibilities for leveraging these...
Article
Full-text available
Cervical cancer is the fourth most common cancer worldwide, and early diagnosis is crucial for successful treatment, as with all types of cancer. The pap-smear test is considered the gold standard for diagnosing cervical cancer. However, the success of diagnosis depends on the expertise and effort of the physician, as with all cancer types. Compute...
Article
Çeltik, temel bir gıda kaynağıdır ve endüstride sıkça kullanılan nadir bitkilerden biridir. Çeltik yaprak hastalıklarının erken teşhisi, ekin hasarını en aza indirmek için büyük önem taşımaktadır. Son yıllarda, derin öğrenme tabanlı bilgisayar destekli sistemler, ziraat sektöründe oldukça önem kazanmış ve çeşitli uygulamalarda etkin rol almıştır. B...
Article
Full-text available
Son yıllarda ortaya çıkan yeni tip Koronavirüs hastalığı (COVID-19), dünya çapında sağlığı tehdit eden ciddi bir hastalık olmuştur. COVID-19 çok hızlı bir şekilde bulaşabilen ve ciddi ölüm artışları ile birçok endişeye zemin hazırlamıştır. Salgının evrensel boyuta taşınmasıyla bu hastalığın erken teşhisine yönelik birçok çalışma yapılmıştır. Erken...
Article
İşaret dili, sağır ve dilsiz bireylerin duygularını, düşüncelerini ve sosyal kimliklerini çevrelerine aktarabilmek için kullandıkları sözsüz bir iletişim aracıdır. İşaret dili, sağır ve dilsiz bireyler ile toplumun geri kalan bireyleri arasındaki iletişimde kilit bir role sahiptir. Normal insanlar arasında işaret dilinin çok yaygın bilinmemesi ve i...
Article
Günümüzde, tarımsal faaliyetlerin verimli hale getirilmesi için her gün birçok araştırma yapılmaktadır. Dünya genelinde kişi başı domates tüketimi, yılda yaklaşık olarak 20 kg ile ilk sıralarda yer almaktadır. Bu nedenle domates üretiminde oluşabilecek hastalıkların tespiti üreticiler için büyük önem arz etmektedir. Hastalıkların çoğu domates yapra...
Article
Full-text available
Breast cancer is one of the deadliest cancer types affecting women worldwide. As with all types of cancer, early detection of breast cancer is of vital importance. Early diagnosis plays an important role in reducing deaths and fighting cancer. Ultrasound (US) imaging is a painless and common technique used in the early detection of breast cancer. I...
Article
Full-text available
Colorectal cancer (CRC) is one of the most common and malignant types of cancer worldwide. Colonoscopy, considered the gold standard for CRC screening, allows immediate removal of polyps, which are precursors to CRC. Many computer-aided diagnosis systems (CADs) have been proposed for automatic polyp detection. Most of these systems are based on tra...
Article
Colorectal cancer (CRC) is one of the common types of cancer with a high mortality rate. Colonoscopy is the gold standard for CRC screening and significantly reduces CRC mortality. However, due to many factors, the rate of missed polyps, which are the precursors of colorectal cancer, is high in practice. Therefore, many artificial intelligence-base...
Article
Colorectal cancer (CRC) is globally the third most common type of cancer. Colonoscopy is considered the gold standard in colorectal cancer screening and allows for the removal of polyps before they become cancerous. Computer-aided detection systems (CADs) have been developed to detect polyps. Unfortunately, these systems have limited sensitivity an...
Article
Deep learning has emerged as a leading machine learning tool in object detection and has attracted attention with its achievements in progressing medical image analysis. Convolutional Neural Networks (CNNs) are the most preferred method of deep learning algorithms for this purpose and they have an essential role in the detection and potential early...

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