Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Transformed Based Deep Neural Network Model to Detect the Conceptual Semantic Relation in Amharic Entities

Creator:
TesTesAdaBel
Publisher:
IEEE
Host:

Visit

doi.org

Languages

Amharic

Licenses

https://doi.org/10.15223/policy-029https://doi.org/10.15223/policy-037

Similar

Semantic Role Labeling for Amharic Text Using Multiple Embeddings and Deep Neural NetworkAUTOMATIC RELATION EXTRACTION BETWEEN ENTITIES FOR AMHARIC TEXTAmharic Character Recognition Using Deep Convolutional Neural NetworkDeep Neural Network model for Underwater Image EnhancementSpeech recognition system based on deep neural network acoustic modeling for low resourced language-AmharicA DEEP LEARNING-BASED ENGLISH TO YORUBA NEURAL TRANSLATION MODEL

Semantic Role Labeling for Amharic Text Using Multiple Embeddings and Deep Neural Network

AUTOMATIC RELATION EXTRACTION BETWEEN ENTITIES FOR AMHARIC TEXT

This research work primarily focused on the automatic relation extraction between entities for Amhar

Amharic Character Recognition Using Deep Convolutional Neural Network

Deep Neural Network model for Underwater Image Enhancement

In recent years, there has been a growing interest in the field of underwater image enhancement, dri

Speech recognition system based on deep neural network acoustic modeling for low resourced language-Amharic

A DEEP LEARNING-BASED ENGLISH TO YORUBA NEURAL TRANSLATION MODEL