Devdiscourse

Agriculture turns to AI: Global trends in land use and crop monitoring

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

Navigating the Code World: The Cutting Edge and Applications of Python in Machine Learning

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...
EE World Online

AI-native chip with integrates 2 MB SRAM, Cortex-M4F CPU and analog sensor interfaces

Ambient Scientific has introduced the GPX10 Pro, a system-on-chip designed specifically for edge AI applications. The device ...
Frontiers

Automated classification of midpalatal suture maturation using 2D convolutional neural networks on CBCT scans

School of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada Introduction: Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, ...
Hosted on MSN

Build A Deep Neural Network From Scratch In Python — No Tensorflow!

Step-by-step coding a full deep neural network with zero libraries — just logic and Python. #NeuralNetwork #PythonCode #DeepLearning Donald Trump's remarks about Putin leave Russian state TV stunned ...
IEEE

Grid Row Parameter Identification Using Tensorflow Convolutional Neural Network

Abstract: Text recognition is an important field of pattern recognition application. In this paper, a joint parameter recognition method based on convolutional neural network is proposed to solve the ...
IEEE

Comparison of Tensorflow and PyTorch in Convolutional Neural Network - based Applications

Abstract: In this paper, we present a comparison between the PyTorch and TensorFlow environments, used in defining neural networks. The purpose is to find whether the choice of a library affects the ...