25 papers · ranked by Valyu relevance
Hyun-Chul Choi, Dominik Sibbing, Leif Kobbelt
We present a nonparametric facial feature localization method using relative directional information between regularly sampled image segments and facial feature points. Instead of using any iterative parameter optimization technique or search algorithm, our method finds the location of facial feature points by using a…
Marco Seeland, Michael Rzanny, Nedal Alaqraa, Jana Wäldchen + 2 more
'Patrick Mäder' 'Yudong Zhang'] Steady improvements of image description methods induced a growing interest in image-based plant species classification, a task vital to the study of biodiversity and ecological sensitivity. Various techniques have been proposed for general object classification over the past years and…
Fintan O'Sullivan, Kirita-Rose Escott, Rachael C. Shaw, Andrew Lensen
This report investigates an unsupervised, feature-based image matching pipeline for the novel application of identifying individual kak¯ a. Applied with a similar- ¯ ity network for clustering, this addresses a weakness of current supervised approaches to identifying individual birds which struggle to handle the…
Riccardo Satta
In video-surveillance, person reidentification is the task of recognising whether an individual has already been observed over a network of cameras. Typically, this is achieved by exploiting the clothing appearance, as classical biometric traits like the face are impractical in real-world video surveillance scenarios.…
Feng Hu
Indoor localization has many applications, such as commercial Location Based Services (LBS), robotic navigation, and assistive navigation for the blind. This paper formulates the indoor localization problem into a multimedia retrieving problem by modeling visual landmarks with a panoramic image feature, and calculating…
Qidan Zhu, Xue Liu, Chengtao Cai
This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial…
Qi Xu, Imee M.A. del Mundo, Maha Zewail-Foote, Brian T. Luke + 2 more
Sequence-level data offers insights into biological processes through the interaction of two or more genomic features from the same or different molecular data types. Within motifs, this interaction is often explored via the co-occurrence of feature genomic tracks using fixed-segments or analytical tests that…
Jehn-Ruey Jiang, Hanas Subakti, Hui-Sung Liang, Sameh Nassar + 1 more
'Aboelmagd Noureldin'] This paper proposes a fingerprint-based indoor localization method, named FPFE (fingerprint feature extraction), to locate a target device (TD) whose location is unknown. Bluetooth low energy (BLE) beacon nodes (BNs) are deployed in the localization area to emit beacon packets periodically. The…
Laura Florea, Corneliu Florea, Constantin Vertan
This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a Multi Layer Perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The…
Peter Kok, Lieke L.F. van Lieshout, Floris P. de Lange
During natural perception, we often form expectations about upcoming input. These expectations are usually multifaceted – we expect a particular object at a particular location. However, expectations about spatial location and stimulus features have mostly been studied in isolation, and it is unclear whether…
Yankun Wang, Hong Fan, Ruizhi Chen, Huan Li + 3 more
'Wu Du'] Locality descriptions are generally communicated using reference objects and spatial relations that reflect human spatial cognition. However, uncertainty is inevitable in locality descriptions. Positioning locality with locality description, with a mapping mechanism between the qualitative and quantitative…
Antonio Anastasio Bruto da Costa, Pallab Dasgupta
In current practice a formal analysis of hybrid system models is assertion-based. The work presented here is based on features that look beyond functional correctness towards a quantitative evaluation of behavioural attributes. A feature defines a real-valued evaluation function over a specific set of traces. This…
Sushrut Thorat, Marius V. Peelen
Feature-based attention modulates visual processing beyond the focus of spatial attention. Previous work has reported such spatially-global effects for low-level features such as color and orientation, as well as for faces. Here, using fMRI, we provide evidence for spatially-global attentional modulation for human…
Arushi Gupta, Alan Moses, Alex X. Lu
Deep learning models are widely used to extract feature representations from microscopy images. While these models are used for single-cell analyses, such as studying single-cell heterogeneity, they typically operate on image crops centered on individual cells with background information present, such as other cells…
Kevin Maik Jablonka, Andrew S. Rosen, Aditi S. Krishnapriyan, Berend Smit
The space of all plausible materials for a given application is so large that it cannot be explored using a brute-force approach. This is, in particular, the case for reticular chemistry which provides materials designers with a practically infinite playground on different length scales. One promising approach to guide…
Su Inn Park, Halil Bisgin, Hongjian Ding, Howard G. Semey + 4 more
'Darryl A. Langley' 'Weida Tong' 'Joshua Xu' 'Jinn-Moon Yang'] A crucial step of food contamination inspection is identifying the species of beetle fragments found in the sample, since the presence of some storage beetles is a good indicator of insanitation or potential food safety hazards. The current pratice, visual…
James C. Moreland, Geoffrey M. Boynton
Feature-based attention can select relevant features such as colors or directions of motion from the visual field irrespective of the spatial position. In visual cortex not only do we see feature-specific attention affecting responses in neurons with receptive fields at an attended location, but that effect also…
Ingmar Kanitscheider, Ila Fiete
Navigation in natural environments is computationally difficult: Location errors from motion estimation noise accumulate over time, while landmarks can be spatially extended and often look alike, thus providing ambiguous data. The brain contains a number of spatially tuned neurons coding for various navigational…
He Sun, Shyam Dwaraknath, Michael E. West, Handong Ling + 2 more
NMR crystallography has emerged as promising technique for the determination and refinement of crystal structures. The crystal structure of compounds containing quadrupolar nuclei, such as 27Al, can be improved by directly comparing solid-state NMR measurements to DFT computations of the electric field gradient (EFG).…
Hang Hu, Jyothsna Padmakumar Bindu, Julia Laskin
Mass spectrometry imaging (MSI) is widely used for the label-free molecular mapping of biological samples. The identification of co-localized molecules in MSI data is crucial to the understanding of biochemical pathways. However, complex MSI data are too large for manual annotation but too small for training deep…
Kevin Mildau, Christoph Büschl, Jürgen Zanghellini, Justin J.J. van der Hooft
Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets…
Steven Torrisi, Matthew Carbone, Brian Rohr, Joseph H. Montoya + 4 more
X-ray absorption spectroscopy (XAS) produces a wealth of information about the local structure of materials, but interpretation of spectra often relies on easily accessible trends and prior assumptions about the structure. Recently, researchers have demonstrated that machine learning models can automate this process to…
Runnan Cao, Jinge Wang, Chujun Lin, Ueli Rutishauser + 4 more
Neurons in the human medial temporal lobe (MTL) that are selective for the identity of specific people are classically thought to encode identity invariant to visual features. However, it remains largely unknown how visual information from higher visual cortex is translated into a semantic representation of an…
Authors not listed
Traditional and non-classical machine learning models for solid-state structure prediction have predominantly relied on compositional features (derived from properties of constituent elements) to predict the existence of structure and its properties. However, the lack of structural information can be a source of…
C. Scott Brown
A Dissertation Submitted to the Graduate Faculty of The University of South Alabama in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computing by Christopher Scott Brown B.S. Mathematics: University of South Alabama 2006 M.S. Mathematics: University of South Alabama 2007 May 2020 []