625 citations · 1.2k across the 22 of their papers we have counts for
15 papers · 1 filter
Towards a Real-Time Facial Analysis System
Bishwo Adhikari, Xingyang Ni, Esa Rahtu +1
Facial analysis is an active research area in computer vision, with many practical applications. Most of the existing studies focus on addressing one specific task and maximizing i…
On the Importance of Encrypting Deep Features
Xingyang Ni, Heikki Huttunen, Esa Rahtu
In this study, we analyze model inversion attacks with only two assumptions: feature vectors of user data are known, and a black-box API for inference is provided. On the one hand,…
using multiple losses for accurate facial age estimation
Yi Zhou, Heikki Huttunen, Tapio Elomaa
Age estimation is an essential challenge in computer vision. With the advances of convolutional neural networks, the performance of age estimation has been dramatically improved. E…
Selective Probabilistic Classifier Based on Hypothesis Testing
Saeed Bakhshi Germi, Esa Rahtu, Heikki Huttunen
In this paper, we propose a simple yet effective method to deal with the violation of the Closed-World Assumption for a classifier. Previous works tend to apply a threshold either…
Sample selection for efficient image annotation
Bishwo Adhikari, Esa Rahtu, Heikki Huttunen
Supervised object detection has been proven to be successful in many benchmark datasets achieving human-level performances. However, acquiring a large amount of labeled image sampl…
Handwritten Character Recognition from Wearable Passive RFID
Leevi Raivio, Han He, Johanna Virkki +1
In this paper we study the recognition of handwritten characters from data captured by a novel wearable electro-textile sensor panel. The data is collected sequentially, such that…
Adaptive L2 Regularization in Person Re-Identification
Xingyang Ni, Liang Fang, Heikki Huttunen
We introduce an adaptive L2 regularization mechanism in the setting of person re-identification. In the literature, it is common practice to utilize hand-picked regularization fact…
Vehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification
Xingyang Ni, Heikki Huttunen
This paper studies vehicle attribute recognition by appearance. In the literature, image-based target recognition has been extensively investigated in many use cases, such as facia…
Elastic Neural Networks for Classification
Yi Zhou, Yue Bai, Shuvra S. Bhattacharyya +1
In this work we propose a framework for improving the performance of any deep neural network that may suffer from vanishing gradients. To address the vanishing gradient issue, we s…
Real Time System for Facial Analysis
Janne Tommola, Pedram Ghazi, Bishwo Adhikari +1
In this paper we describe the anatomy of a real-time facial analysis system. The system recognizes the age, gender and facial expression from users in appearing in front of the cam…
Classification of Building Information Model (BIM) Structures with Deep Learning
Francesco Lomio, Ricardo Farinha, Mauri Laasonen +1
In this work we study an application of machine learning to the construction industry and we use classical and modern machine learning methods to categorize images of building desi…
Embedded Implementation of a Deep Learning Smile Detector
Pedram Ghazi, Antti P. Happonen, Jani Boutellier +1
In this paper we study the real time deployment of deep learning algorithms in low resource computational environments. As the use case, we compare the accuracy and speed of neural…
Faster Bounding Box Annotation for Object Detection in Indoor Scenes
Bishwo Adhikari, Jukka Peltomäki, Jussi Puura +1
This paper proposes an approach for rapid bounding box annotation for object detection datasets. The procedure consists of two stages: The first step is to annotate a part of the d…
Elastic Neural Networks: A Scalable Framework for Embedded Computer Vision
Yue Bai, Shuvra S. Bhattacharyya, Antti P. Happonen +1
We propose a new framework for image classification with deep neural networks. The framework introduces intermediate outputs to the computational graph of a network. This enables f…
Car Type Recognition with Deep Neural Networks
Heikki Huttunen, Fatemeh Shokrollahi Yancheshmeh, Ke Chen
In this paper we study automatic recognition of cars of four types: Bus, Truck, Van and Small car. For this problem we consider two data driven frameworks: a deep neural network an…