36 citations · 49 across the 8 of their papers we have counts for
8 papers
KnifeHunter: Structured Local Representation Learning for Fine-Grained Knife Image Retrieval in Law Enforcement
Syed Sameed Husain, Eng-Jon Ong, Stephen Simpson +3
Knife-enabled violence presents a major public safety challenge, and law enforcement agencies require scalable tools for catalogue-level knife identification, intelligence analysis…
A Universal Nearest-Neighbor Estimator for Intrinsic Dimensionality
Eng-Jon Ong, Omer Bobrowski, Gesine Reinert +1
Estimating the intrinsic dimensionality (ID) of data is a fundamental problem in machine learning and computer vision, providing insight into the true degrees of freedom underlying…
Single-cell Subcellular Protein Localisation Using Novel Ensembles of Diverse Deep Architectures
Syed Sameed Husain, Eng-Jon Ong, Dmitry Minskiy +3
Unravelling protein distributions within individual cells is key to understanding their function and state and indispensable to developing new treatments. Here we present the Hybri…
Understanding the Distributions of Aggregation Layers in Deep Neural Networks
Eng-Jon Ong, Sameed Husain, Miroslaw Bober
The process of aggregation is ubiquitous in almost all deep nets models. It functions as an important mechanism for consolidating deep features into a more compact representation,…
ACTNET: end-to-end learning of feature activations and multi-stream aggregation for effective instance image retrieval
Syed Sameed Husain, Eng-Jon Ong, Miroslaw Bober
We propose a novel CNN architecture called ACTNET for robust instance image retrieval from large-scale datasets. Our key innovation is a learnable activation layer designed to impr…
Deep Architectures and Ensembles for Semantic Video Classification
Eng-Jon Ong, Sameed Husain, Mikel Bober-Irizar +1
This work addresses the problem of accurate semantic labelling of short videos. To this end, a multitude of different deep nets, ranging from traditional recurrent neural networks…