Muhammad Osama

BTech(MechEng)

Mechanical Engineering with specialization in AI & Robotics

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence. Muhammad has worked on various research projects related to data analytics, machine learning, and deep learning for industries such as retail, medical, finance, agriculture, and Ed-Tech. He is enthusiastic and passionate about Artificial Intelligence-related research. Outside of work, he enjoys learning about new developments across all the fields related to science, technology, engineering, mathematics, and statistics.

Articles from Muhammad

RST-Net: Advancing Plant Disease Prediction Using Enlightened Swin Transformer Networks

Researchers introduced RST-Net, a novel deep learning model for plant disease prediction, combining residual convolutional networks and Swin transformers. Testing on a benchmark dataset showed superior performance over state-of-the-art models, with potential applications in smart agriculture and precision farming.

24 Apr 2024

YOLOv8-PG: Lightweight and Efficient Model for Pigeon Egg Detection

Chinese researchers present YOLOv8-PG, a lightweight convolutional neural network tailored for accurate detection of real and fake pigeon eggs in challenging environments. By refining key model components and leveraging a novel loss function, YOLOv8-PG outperforms existing models in accuracy while maintaining efficiency, offering promising applications for automated egg collection in pigeon breeding.

23 Apr 2024

Automating Information Extraction in Criminal Investigations Using a Hybrid Classification Model

Researchers developed a hybrid classification model to autonomously extract crucial information from legal documents, achieving superior accuracy in comparison to baseline models. Leveraging GPT-3.5 and employing prompt strategies, the model demonstrated efficiency in extracting key information from murder verdicts, offering a promising tool to enhance investigative workflows and decision-making in criminal investigations.

22 Apr 2024

Advancements in Electrodes for Wearable Skin Devices

The article explores electrode design for wearable skin devices, crucial for health monitoring and human-machine interfaces. It discusses properties like flexibility and conductivity and proposes methods like structure modification and hybrid materials. Applications range from health monitoring to therapy and human-machine interfaces, emphasizing the need for innovative electrode design to enhance device performance and integration with AI for smarter functionalities.

20 Apr 2024

AI-Driven Enhancement of Retinal Pigment Epithelial Cell Visualization Using Adaptive OCT

Researchers developed a novel AI method, P-GAN, to improve the visualization of retinal pigment epithelial (RPE) cells using adaptive optics optical coherence tomography (AO-OCT). By transforming single noisy images into detailed representations of RPE cells, this approach enhances contrast and reduces imaging time, potentially revolutionizing ophthalmic diagnostics and personalized treatment strategies for retinal conditions.

18 Apr 2024

Enhanced PSO Algorithm for Engineering Problems

Researchers introduced the NDWPSO algorithm, enhancing PSO's performance for engineering optimization. Integrating various strategies like dynamic inertia weight, adaptive acceleration coefficients, and innovative initialization schemes, NDWPSO demonstrated superior convergence speed and solution accuracy.

17 Apr 2024

Machine Learning Analysis of Urban Residential Water Consumption in Developing Countries

Researchers employed machine learning techniques to analyze residential water consumption patterns in Adama City, Ethiopia, highlighting factors influencing water usage. Findings emphasized low per capita usage rates and the need for infrastructure improvements. ML models identified key determinants and suggested targeted interventions for promoting water conservation and sustainability.

16 Apr 2024

Sentiment Analysis Reveals Public Perceptions of Coronary Artery Calcium Testing

Researchers employed AI techniques to analyze Reddit discussions on coronary artery calcium (CAC) testing, revealing diverse sentiments and concerns. The study identified 91 topics and 14 discussion clusters, indicating significant interest and engagement. While sentiment analysis showed predominantly neutral or slightly negative attitudes, there was a decline in sentiment over time.

15 Apr 2024

Remote Homologous Protein Detection Using Protein Language Model Search

Researchers introduced Protein Language Model Search (PLMSearch), a method designed to improve sensitivity and accuracy in detecting remote homologous proteins. Leveraging deep representations from a pre-trained protein language model, PLMSearch effectively identifies evolutionary relationships solely based on sequence information.

12 Apr 2024

Small Target Detection in UAV Aerial Images with a Multi-Scale Detection Network

Researchers from China proposed an innovative method to improve the accuracy of detecting small targets in aerial images captured by unmanned aerial vehicles (UAVs). By introducing a multi-scale detection network that combines different feature information levels, the study aimed to enhance detection accuracy while reducing interference from image backgrounds.

11 Apr 2024