research
∙
05/11/2023
OneCAD: One Classifier for All image Datasets using multimodal learning
Vision-Transformers (ViTs) and Convolutional neural networks (CNNs) are ...
share
research
∙
05/26/2022
Reinforcement Learning Approach for Mapping Applications to Dataflow-Based Coarse-Grained Reconfigurable Array
The Streaming Engine (SE) is a Coarse-Grained Reconfigurable Array which...
research
∙
02/08/2020
Capsule Network Performance with Autonomous Navigation
Capsule Networks (CapsNets) have been proposed as an alternative to Conv...
research
∙
05/24/2019
Continual Reinforcement Learning in 3D Non-stationary Environments
High-dimensional always-changing environments constitute a hard challeng...
research
∙
05/19/2018
Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition
Inspired by "predictive coding" - a theory in neuroscience, we develop a...
research
∙
02/13/2018
Deep Predictive Coding Network for Object Recognition
Inspired by predictive coding in neuroscience, we designed a bi-directio...
research
∙
08/08/2017
Snowflake: A Model Agnostic Accelerator for Deep Convolutional Neural Networks
Deep convolutional neural networks (CNNs) are the deep learning model of...
research
∙
06/14/2017
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
Pixel-wise semantic segmentation for visual scene understanding not only...
research
∙
06/08/2017
CortexNet: a Generic Network Family for Robust Visual Temporal Representations
In the past five years we have observed the rise of incredibly well perf...
research
∙
06/07/2016
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
The ability to perform pixel-wise semantic segmentation in real-time is ...
research
∙
05/24/2016
An Analysis of Deep Neural Network Models for Practical Applications
Since the emergence of Deep Neural Networks (DNNs) as a prominent techni...
research
∙
11/17/2015
Recurrent Neural Networks Hardware Implementation on FPGA
Recurrent Neural Networks (RNNs) have the ability to retain memory and l...
research
∙
12/17/2014
Flattened Convolutional Neural Networks for Feedforward Acceleration
We present flattened convolutional neural networks that are designed for...
research
∙
06/01/2013
An Analysis of the Connections Between Layers of Deep Neural Networks
We present an analysis of different techniques for selecting the connect...
research
∙
01/13/2013
Clustering Learning for Robotic Vision
We present the clustering learning technique applied to multi-layer feed...
research
∙
09/12/2012