most citedSimplified Long Short-term Memory Recurrent Neural Networks: part III

6 citations · 12 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG20241 cited

MetaPix: A Data-Centric AI Development Platform for Efficient Management and Utilization of Unstructured Computer Vision Data

Sai Vishwanath Venkatesh, Atra Akandeh, Madhu Lokanath

In today's world of advanced AI technologies, data management is a critical component of any AI/ML solution. Effective data management is vital for the creation and maintenance of…

cs.CV2022

Sentence-Level Sign Language Recognition Framework

Atra Akandeh

We present two solutions to sentence-level SLR. Sentence-level SLR required mapping videos of sign language sentences to sequences of gloss labels. Connectionist Temporal Classific…

cs.NE2019

Slim LSTM networks: LSTM_6 and LSTM_C6

Atra Akandeh, Fathi M. Salem

We have shown previously that our parameter-reduced variants of Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNN) are comparable in performance to the standard LSTM RNN…

cs.NE20176 cited

Simplified Long Short-term Memory Recurrent Neural Networks: part III

Atra Akandeh, Fathi M. Salem

This is part III of three-part work. In parts I and II, we have presented eight variants for simplified Long Short Term Memory (LSTM) recurrent neural networks (RNNs). It is noted…

cs.NE20174 cited

Simplified Long Short-term Memory Recurrent Neural Networks: part II

Atra Akandeh, Fathi M. Salem

This is part II of three-part work. Here, we present a second set of inter-related five variants of simplified Long Short-term Memory (LSTM) recurrent neural networks by further re…

cs.NE20172 cited

Simplified Long Short-term Memory Recurrent Neural Networks: part I

Atra Akandeh, Fathi M. Salem

We present five variants of the standard Long Short-term Memory (LSTM) recurrent neural networks by uniformly reducing blocks of adaptive parameters in the gating mechanisms. For s…