17 citations · 43 across the 12 of their papers we have counts for
13 papers
Dataset for Real-World Human Action Detection Using FMCW mmWave Radar
Dylan jayabahu, Parthipan Siva
Human action detection using privacy-preserving mmWave radar sensors is studied for its applications in healthcare and home automation. Unlike existing research, limited to simulat…
Step length measurement in the wild using FMCW radar
Parthipan Siva, Alexander Wong, Patricia Hewston +5
With an aging population, numerous assistive and monitoring technologies are under development to enable older adults to age in place. To facilitate aging in place predicting risk…
Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis
Devinder Kumar, Parthipan Siva, Paul Marchwica +1
An ongoing major challenge in computer vision is the task of person re-identification, where the goal is to match individuals across different, non-overlapping camera views. While…
Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID
Devinder Kumar, Parthipan Siva, Paul Marchwica +1
Person re-identification (ReID) remains a very difficult challenge in computer vision, and critical for large-scale video surveillance scenarios where an individual could appear in…
Exploiting Prunability for Person Re-Identification
Hugo Masson, Amran Bhuiyan, Le Thanh Nguyen-Meidine +4
Recent years have witnessed a substantial increase in the deep learning (DL)architectures proposed for visual recognition tasks like person re-identification,where individuals must…
An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identification
Paul Marchwica, Michael Jamieson, Parthipan Siva
In recent years, a variety of proposed methods based on deep convolutional neural networks (CNNs) have improved the state of the art for large-scale person re-identification (ReID)…
Transfer Learning by Ranking for Weakly Supervised Object Annotation
Zhiyuan Shi, Parthipan Siva, Tao Xiang
Most existing approaches to training object detectors rely on fully supervised learning, which requires the tedious manual annotation of object location in a training set. Recently…
NeRD: a Neural Response Divergence Approach to Visual Salience Detection
M. J. Shafiee, P. Siva, C. Scharfenberger +2
In this paper, a novel approach to visual salience detection via Neural Response Divergence (NeRD) is proposed, where synaptic portions of deep neural networks, previously trained…
Scene Invariant Crowd Segmentation and Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG)
Parthipan Siva, Mohammad Javad Shafiee, Mike Jamieson +1
The problem of automated crowd segmentation and counting has garnered significant interest in the field of video surveillance. This paper proposes a novel scene invariant crowd seg…
Domain Adaptation and Transfer Learning in StochasticNets
Mohammad Javad Shafiee, Parthipan Siva, Paul Fieguth +1
Transfer learning is a recent field of machine learning research that aims to resolve the challenge of dealing with insufficient training data in the domain of interest. This is a…
Efficient Deep Feature Learning and Extraction via StochasticNets
Mohammad Javad Shafiee, Parthipan Siva, Paul Fieguth +1
Deep neural networks are a powerful tool for feature learning and extraction given their ability to model high-level abstractions in highly complex data. One area worth exploring i…
StochasticNet: Forming Deep Neural Networks via Stochastic Connectivity
Mohammad Javad Shafiee, Parthipan Siva, Alexander Wong
Deep neural networks is a branch in machine learning that has seen a meteoric rise in popularity due to its powerful abilities to represent and model high-level abstractions in hig…
A deep-structured fully-connected random field model for structured inference
Alexander Wong, Mohammad Javad Shafiee, Parthipan Siva +1
There has been significant interest in the use of fully-connected graphical models and deep-structured graphical models for the purpose of structured inference. However, fully-conn…