Muhammad Fazal Ijaz
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View article: Land Cover Classification for Identifying the Agriculture Fields Using Versions of YOLO V8
Land Cover Classification for Identifying the Agriculture Fields Using Versions of YOLO V8 Open
Accurate identification and classification of agricultural fields is essential for analyzing crop growth, agricultural resource management, and supporting decision-making in precision farming. The current study uses the remote sensing imag…
View article: A multi-patch-based deep learning model with VGG19 for breast cancer classifications in the pathology images
A multi-patch-based deep learning model with VGG19 for breast cancer classifications in the pathology images Open
Purpose Breast cancer encompasses various subtypes with distinct prognoses, necessitating accurate stratification methods. Current techniques rely on quantifying gene expression in limited subsets. Given the complexity of breast tissues, e…
View article: Advanced CNN models in gastric cancer diagnosis: enhancing endoscopic image analysis with deep transfer learning
Advanced CNN models in gastric cancer diagnosis: enhancing endoscopic image analysis with deep transfer learning Open
Introduction The rapid advancement of science and technology has significantly expanded the capabilities of artificial intelligence, enhancing diagnostic accuracy for gastric cancer. Methods This research aims to utilize endoscopic images …
View article: Enhancing medical image classification via federated learning and pre-trained model
Enhancing medical image classification via federated learning and pre-trained model Open
The precise classification of medical images is crucial in various healthcare applications, especially in fields like disease diagnosis and treatment planning. In recent times, machine-intelligent models are desired to work in remote setti…
View article: PrecisionLymphoNet: Advancing Malignant Lymphoma Diagnosis via Ensemble Transfer Learning with CNNs
PrecisionLymphoNet: Advancing Malignant Lymphoma Diagnosis via Ensemble Transfer Learning with CNNs Open
Malignant lymphoma, which impacts the lymphatic system, presents diverse challenges in accurate diagnosis due to its varied subtypes—chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and mantle cell lymphoma (MCL). Lymphoma is …
View article: FedHealthFog: A federated learning-enabled approach towards healthcare analytics over fog computing platform
FedHealthFog: A federated learning-enabled approach towards healthcare analytics over fog computing platform Open
The emergence of federated learning (FL) technique in fog-enabled healthcare system has leveraged enhanced privacy towards safeguarding sensitive patient information over heterogeneous computing platforms. In this paper, we introduce the F…
View article: Editorial: Recent advances in big data, machine, and deep learning for precision agriculture
Editorial: Recent advances in big data, machine, and deep learning for precision agriculture Open
Keywords: precision agriculture (PA), big data & analytics, machine learning, plant disease, technology
View article: Editorial: Recent Advances in Deep Learning and Medical Imaging for Cancer Treatment
Editorial: Recent Advances in Deep Learning and Medical Imaging for Cancer Treatment Open
In the evolving landscape of medical imaging, the escalating need for deep-learningmethods takes center stage, offering the capability to autonomously acquire abstract datarepresentations crucial for early detection and classification for …
View article: AI-Driven Digital Twin Model for Reliable Lithium-Ion Battery Discharge Capacity Predictions
AI-Driven Digital Twin Model for Reliable Lithium-Ion Battery Discharge Capacity Predictions Open
The present study proposes a novel method for predicting the discharge capabilities of lithium-ion (Li-ion) batteries using a digital twin model in practice. By combining cutting-edge machine learning techniques, such as AdaBoost and long …
View article: Shortcut Learning Explanations for Deep Natural Language Processing: A Survey on Dataset Biases
Shortcut Learning Explanations for Deep Natural Language Processing: A Survey on Dataset Biases Open
The introduction of pre-trained large language models (LLMs) has transformed NLP by fine-tuning task-specific datasets, enabling notable advancements in news classification, language translation, and sentiment analysis. This has revolution…
View article: Corrections to “ERDeR: The Combination of Statistical Shrinkage Methods and Ensemble Approaches to Improve the Performance of Deep Regression”
Corrections to “ERDeR: The Combination of Statistical Shrinkage Methods and Ensemble Approaches to Improve the Performance of Deep Regression” Open
Presents corrections to the paper, ERDeR: The Combination of Statistical Shrinkage Methods and Ensemble Approaches to Improve the Performance of Deep Regression.
View article: ERDeR: The Combination of Statistical Shrinkage Methods and Ensemble Approaches to Improve the Performance of Deep Regression
ERDeR: The Combination of Statistical Shrinkage Methods and Ensemble Approaches to Improve the Performance of Deep Regression Open
Ensembling is a powerful technique to obtain the most accurate results. In some cases, the large number of learners in ensemble learning mostly increases both computational load during the test phase and error rate. To solve this problem, …
View article: Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data
Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data Open
Fetal health care is vital in ensuring the health of pregnant women and the fetus. Regular check-ups need to be taken by the mother to determine the status of the fetus' growth and identify any potential problems. To know the status of the…
View article: Impact of Acquisition of Digital Skills on Perceived Employability of Youth: Mediating Role of Course Quality
Impact of Acquisition of Digital Skills on Perceived Employability of Youth: Mediating Role of Course Quality Open
Penang Youth Development Corporation took the “Penang Young Digital Talent Program” initiative to bridge the gap between Malaysian youth’s current digital skills and emerging technologies market demands. The program comprises different onl…
View article: Associative Discussion Among Generating Adversarial Samples Using Evolutionary Algorithm and Samples Generated Using GAN
Associative Discussion Among Generating Adversarial Samples Using Evolutionary Algorithm and Samples Generated Using GAN Open
The remarkable accomplishments of deep neural networks (DNN) have led to their widespread adoption in various contexts, including safety-critical applications. Many strategies have been implemented to generate adversarial samples using DNN…
View article: Classification of Mental Stress from Wearable Physiological Sensors Using Image-Encoding-Based Deep Neural Network
Classification of Mental Stress from Wearable Physiological Sensors Using Image-Encoding-Based Deep Neural Network Open
The human body is designed to experience stress and react to it, and experiencing challenges causes our body to produce physical and mental responses and also helps our body to adjust to new situations. However, stress becomes a problem wh…
View article: Using Recurrent Neural Networks for Predicting Type-2 Diabetes from Genomic and Tabular Data
Using Recurrent Neural Networks for Predicting Type-2 Diabetes from Genomic and Tabular Data Open
The development of genomic technology for smart diagnosis and therapies for various diseases has lately been the most demanding area for computer-aided diagnostic and treatment research. Exponential breakthroughs in artificial intelligence…