Tree Species Identification in Urban Environments Using TensorFlow Lite and a Transfer Learning Approach

XES Tensorflow - Process Prediction using the Tensorflow Deep-Learning Framework

Predicting the next activity of a running process is an important aspect of process management. Recently, artificial neural networks, so called deep-learning approaches, have been proposed to address this challenge. This demo paper describes a software application that applies the Tensorflow deep-learning framework to process prediction. The software application reads industry-standard XES file...

Identification Psychological Disorders Based on Data in Virtual Environments Using Machine Learning

Introduction: Psychological disorders is one of the most problematic and important issue in today's society. Early prognosis of these disorders matters because receiving professional help at the appropriate time could improve the quality of life of these patients. Recently, researches use social media as a form of new tools in identifying psychological disorder. It seems that through the use of...

TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

We introduce TensorFlow Agents, an efficient infrastructure paradigm for building parallel reinforcement learning algorithms in TensorFlow. We simulate multiple environments in parallel, and group them to perform the neural network computation on a batch rather than individual observations. This allows the TensorFlow execution engine to parallelize computation, without the need for manual synch...

Urban tree species mapping using hyperspectral and lidar data fusion

eplicitation in interlingual and intralingual translations of shahnameh ferdowsi: a text linguistic approach

بررسی و مقایسه تفاوتها و شباهت های ترجمه ی درون زبانی و برون زبانی با تمرکز بر زبانشناسی متن. برای امر مقایسه میزان بسامد تصریح به کار رفته در ترجمه ی درون زبانی و نیز برون زبانی شاهنامه ی فردوسی مورد بررسی قرار گرفت.