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Visualizing a magnetic field model with Python
Learn how to visualize a magnetic field model using Python! 🧲💻 In this tutorial, we’ll walk through creating a 2D vector field to represent the magnetic forces around a dipole. Perfect for physics ...
Abstract: Alzheimer's disease is a progressive neurological disorder that primarily impacts memory, cognition, and behavior, making it the leading cause of dementia in older adults. Timely and ...
OpenAI says GPT‑5.2 is smarter than ever — but can it actually handle complex reasoning, code, planning and synthesis? I ...
Abstract: Image captioning enables computers understand and interpret visual content by bridging the gap between natural language processing and computer vision. The model proposed in this paper for ...
Google AI Plus affordable plan has launched in India this week and it competes directly with the OpenAI ChatGPT Go plan ...
Abstract: Handwritten Amharic character recognition presents significant challenges due to the script’s syllabic nature and variations in handwriting styles. This study investigates a hybrid approach ...
Abstract: This research work suggests a quick way to sort histopathological pictures of lung and colon cancers by using two deep learning models: a custom CNN and EfficientNetB3. In this respect, the ...
Overview: Keras remains one of the most intuitive and developer-friendly frameworks for building deep learning models, making ...
Official PyTorch implementation of YOLOE. ICCV 2025. Comparison of performance, training cost, and inference efficiency between YOLOE (Ours) and YOLO-Worldv2 in terms of open text prompts.
Advanced CNN-RNN Model Based Automatic Modulation Classification on Resource-Constrained End Devices
Abstract: In this paper, we propose a hybrid convolutional recurrent neural network (CNN-RNN) model to operate on resource-constrained end (RCE) devices for automatic modulation classification (AMC).
Abstract: Coronary Heart Disease popularly referred to as CHD is one of the leading causes of death and illness across the global population making it imperative for the identification of an effective ...
Abstract: Driver drowsiness and fatigue are significant road safety risks, leading to numerous accidents globally. This research presents a comparative analysis of Convolutional Neural Network (CNN) ...
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