Search Results for author:
Found 5 papers, 1 papers with code
EncodeNet: A Framework for Boosting DNN Accuracy with Entropy-driven Generalized Converting Autoencoder
Our experimental results demonstrate that EncodeNet improves the accuracy of VGG16 from 92. 64% to 94. 05% on CIFAR-10 and RestNet20 from 74. 56% to 76. 04% on CIFAR-100.
A Survey on 3D Egocentric Human Pose Estimation
Egocentric human pose estimation aims to estimate human body poses and develop body representations from a first-person camera perspective.
A Converting Autoencoder Toward Low-latency and Energy-efficient DNN Inference at the Edge
We present CBNet, a low-latency and energy-efficient DNN inference framework tailored for edge devices.
Generalized Zero-Shot Learning using Multimodal Variational Auto-Encoder with Semantic Concepts
To overcome this problem, we propose a Multimodal Variational Auto-Encoder (M-VAE) which can learn the shared latent space of image features and the semantic space.
Show Why the Answer is Correct! Towards Explainable AI using Compositional Temporal Attention
This results in achieving better understanding of complex questions and also provides reasoning as to why the module predicts a particular answer.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
