8 hasil untuk "Muhammad Shadab Alam Hashmi"
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Artikel Jurnal
A Sentence-Level Encoder–Decoder Architecture for Designing an Administrative Roman Urdu Chatbot
This research focuses on developing an intelligent administrative chatbot for Roman Urdu to overcome the language barrier that hinders individuals who are not fluent in English from utilizing existing chatbot frameworks. While chatbot architectures can be rule based or artificial intelligence (AI)…
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Heart failure survival prediction using novel transfer learning based probabilistic features
Heart failure is a complex cardiovascular condition characterized by the heart’s inability to pump blood effectively, leading to a cascade of physiological changes. Predicting survival in heart failure patients is crucial for optimizing patient care and resource allocation. This research aims to…
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Artikel Jurnal
Dual-modality fusion for mango disease classification using dynamic attention based ensemble of leaf & fruit images
Abstract Mango is one of the most beloved fruits and plays an indispensable role in the agricultural economies of many tropical countries like Pakistan, India, and other Southeast Asian countries. Similar to other fruits, mango cultivation is also threatened by various diseases, including…
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Artikel Jurnal
Website Phishing Attack Detection Using Innovative Meta Learning-Based Ensemble Approach
Phishing remains the most pervasive cybersecurity threat, exploiting human vulnerabilities through sophisticated social engineering. While traditional heuristic and blacklist-based solutions struggle against evolving attacks, this paper proposes a novel stacked ensemble model combining Artificial…
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Novel Ensemble Learning Algorithm for Early Detection of Lower Back Pain Using Spinal Anomalies
Lower back pain (LBP) is a musculoskeletal condition that affects millions of people worldwide and significantly limits their mobility and daily activities. Appropriate ergonomics and exercise are crucial preventive measures that play a vital role in managing and reducing the risk of LBP…
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Railway Track Inspection Using Deep Learning Based on Audio to Spectrogram Conversion: An on-the-Fly Approach
The periodic inspection of railroad tracks is very important to find structural and geometrical problems that lead to railway accidents. Currently, in Pakistan, rail tracks are inspected by an acoustic-based manual system that requires a railway engineer as a domain expert to differentiate between…
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Artikel Jurnal
VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification
Although coffee is a crucial commodity for developing nations’ economies, processing defects can significantly impact the safety, commercial value, and quality of coffee beans. Traditional coffee bean grading methods are labor-intensive and prone to error, necessitating automated and accurate…
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Artikel Jurnal Teks lengkap
Railway Track Fault Detection Using Selective MFCC Features from Acoustic Data
Railway track faults may lead to railway accidents and cause human and financial loss. Spatial, temporal, and weather elements, and wear and tear, lead to ballast, loose nuts, misalignment, and cracks leading to accidents. Manual inspection of such defects is time-consuming and prone to errors…