Search Results for author: Dimitrios Stamoulis

Found 9 papers, 3 papers with code

Stable Diffusion For Aerial Object Detection

no code implementations21 Nov 2023 Yanan Jian, Fuxun Yu, Simranjit Singh, Dimitrios Stamoulis

Aerial object detection is a challenging task, in which one major obstacle lies in the limitations of large-scale data collection and the long-tail distribution of certain classes.

Data Augmentation Object +2

Third ArchEdge Workshop: Exploring the Design Space of Efficient Deep Neural Networks

no code implementations22 Nov 2020 Fuxun Yu, Dimitrios Stamoulis, Di Wang, Dimitrios Lymberopoulos, Xiang Chen

This paper gives an overview of our ongoing work on the design space exploration of efficient deep neural networks (DNNs).

Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization

1 code implementation1 Jul 2019 Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu

In this work, we alleviate the NAS search cost down to less than 3 hours, while achieving state-of-the-art image classification results under mobile latency constraints.

Hyperparameter Optimization Image Classification +1

Single-Path NAS: Device-Aware Efficient ConvNet Design

no code implementations10 May 2019 Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu

Can we automatically design a Convolutional Network (ConvNet) with the highest image classification accuracy under the latency constraint of a mobile device?

General Classification Image Classification +1

Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours

9 code implementations5 Apr 2019 Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu

Can we automatically design a Convolutional Network (ConvNet) with the highest image classification accuracy under the runtime constraint of a mobile device?

General Classification Image Classification +1

Hardware-Aware Machine Learning: Modeling and Optimization

no code implementations14 Sep 2018 Diana Marculescu, Dimitrios Stamoulis, Ermao Cai

What is the latency or energy cost for an inference made by a Deep Neural Network (DNN)?

BIG-bench Machine Learning

Designing Adaptive Neural Networks for Energy-Constrained Image Classification

no code implementations5 Aug 2018 Dimitrios Stamoulis, Ting-Wu Chin, Anand Krishnan Prakash, Haocheng Fang, Sribhuvan Sajja, Mitchell Bognar, Diana Marculescu

We cast the design of adaptive CNNs as a hyper-parameter optimization problem with respect to energy, accuracy, and communication constraints imposed by the mobile device.

Bayesian Optimization Classification +2

HyperPower: Power- and Memory-Constrained Hyper-Parameter Optimization for Neural Networks

no code implementations6 Dec 2017 Dimitrios Stamoulis, Ermao Cai, Da-Cheng Juan, Diana Marculescu

While selecting the hyper-parameters of Neural Networks (NNs) has been so far treated as an art, the emergence of more complex, deeper architectures poses increasingly more challenges to designers and Machine Learning (ML) practitioners, especially when power and memory constraints need to be considered.

Bayesian Optimization

NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks

2 code implementations15 Oct 2017 Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis, Diana Marculescu

We also propose the "energy-precision ratio" (EPR) metric to guide machine learners in selecting an energy-efficient CNN architecture that better trades off the energy consumption and prediction accuracy.

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