There are effective approaches for 2D segmentation, yet 3D cell segmentation remains a critical bottleneck due to diverse cell morphologies, low signal-to-noise ratios, and data scarcity. We introduce ...

Self-IntroductionNice to meet you. I am Saito, and I joined Morgenrot in September 2026.I have worked as an infrastructure engineer on projects at various phases. In my previous job, I handled many ...

FastAPI provides a quick way to build a backend service with Python. With a few decorators, you can turn your Python function into an API application. It is widely used by many companies including ...

Abstract: This work presents the development of a custom convolutional neural network (CNN) architecture for image classification, efficiently implemented on a hardware platform such as the Raspberry ...

Abstract: Recent advancements in computer vision and deep learning have significantly enhanced the potential for image-based bird species identification, garnering considerable interest in ornithology ...

This code pattern demonstrates how images, specifically document images like id cards, application forms, cheque leaf, can be classified using Convolutional Neural Network (CNN). Even though there are ...

This project consists of following steps: - dataset creation with web scraping (BeautifulSoup) - data pre-processing (DifPy, Rembg, Keras) - CNN deep learning model training (used MobileNet V2 model) ...