1.5k citations · 4.1k across the 18 of their papers we have counts for
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OneCAD: One Classifier for All image Datasets using multimodal learning
Shakti N. Wadekar, Eugenio Culurciello
Vision-Transformers (ViTs) and Convolutional neural networks (CNNs) are widely used Deep Neural Networks (DNNs) for classification task. These model architectures are dependent on…
Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition
Kuan Han, Haiguang Wen, Yizhen Zhang +3
Inspired by "predictive coding" - a theory in neuroscience, we develop a bi-directional and dynamic neural network with local recurrent processing, namely predictive coding network…
Deep Predictive Coding Network for Object Recognition
Haiguang Wen, Kuan Han, Junxing Shi +3
Based on the predictive coding theory in neuroscience, we designed a bi-directional and recurrent neural net, namely deep predictive coding networks (PCN). It has feedforward, feed…
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
Abhishek Chaurasia, Eugenio Culurciello
Pixel-wise semantic segmentation for visual scene understanding not only needs to be accurate, but also efficient in order to find any use in real-time application. Existing algori…
CortexNet: a Generic Network Family for Robust Visual Temporal Representations
Alfredo Canziani, Eugenio Culurciello
In the past five years we have observed the rise of incredibly well performing feed-forward neural networks trained supervisedly for vision related tasks. These models have achieve…
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Adam Paszke, Abhishek Chaurasia, Sangpil Kim +1
The ability to perform pixel-wise semantic segmentation in real-time is of paramount importance in mobile applications. Recent deep neural networks aimed at this task have the disa…
An Analysis of Deep Neural Network Models for Practical Applications
Alfredo Canziani, Adam Paszke, Eugenio Culurciello
Since the emergence of Deep Neural Networks (DNNs) as a prominent technique in the field of computer vision, the ImageNet classification challenge has played a major role in advanc…
An Analysis of the Connections Between Layers of Deep Neural Networks
Eugenio Culurciello, Jonghoon Jin, Aysegul Dundar +1
We present an analysis of different techniques for selecting the connection be- tween layers of deep neural networks. Traditional deep neural networks use ran- dom connection table…
Clustering Learning for Robotic Vision
Eugenio Culurciello, Jordan Bates, Aysegul Dundar +2
We present the clustering learning technique applied to multi-layer feedforward deep neural networks. We show that this unsupervised learning technique can compute network filters…
Visual Tracking with Similarity Matching Ratio
Aysegul Dundar, Jonghoon Jin, Eugenio Culurciello
This paper presents a novel approach to visual tracking: Similarity Matching Ratio (SMR). The traditional approach of tracking is minimizing some measures of the difference between…