Browsing The College of Engineering and Computer Science by Title
Now showing items 1-20 of 184
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Absorbance biosensors‐based hybrid MoS2 nanosheets for Escherichia coli detection
(2023-06-23)Detecting Escherichia coli is essential in biomedical, environmental, and food safety applications. In this paper, we have developed a simple, rapid, sensitive, and selective E. coli DNA sensor based on the novel hybrid-type ... -
Absorbance biosensors‑based hybrid MoS2 nanosheets for Escherichia coli detection
(2023)Detecting Escherichia coli is essential in biomedical, environmental, and food safety applications. In this paper, we have developed a simple, rapid, sensitive, and selective E. coli DNA sensor based on the novel hybrid-type ... -
An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
(2022-08-06)Interpretation of chest radiographs (CXR) is a difficult but essential task for detecting thoracic abnormalities. Recent artificial intelligence (AI) algorithms have achieved radiologist-level performance on various medical ... -
An accurate and explainable deep learning system improves interobserver agreement in the interpretation of chest radiograph
(2022-10-04)Interpretation of chest radiographs (CXR) is a difficult but essential task for detecting thoracic abnormalities. Recent artificial intelligence (AI) algorithms have achieved radiologist-level performance on various medical ... -
Active Temperature Compensation for MEMS Capacitive Sensor
(2021-09-01)Temperature variations are one of the most crucial factors that need to be compensated for in MEMS sensors. Many traditional methodologies require an additional circuit to compensate for temperature. This work describes a ... -
Adaptive Proxy Anchor Loss for Deep Metric Learning
(2022-10)Deep metric learning (or simply called metric learning) uses the deep neural network to learn the representation of images, leading to widely used in many applications, e.g. image retrieval and face recognition. In the ... -
Adoption of IP Truncation in a Privacy-Based Decision Tree Pruning Design: A Case Study in Network Intrusion Detection System
(2022-03)A decision tree is a transparent model where the rules are visible and can represent the logic of classification. However, this structure might allow attackers to infer confidential information if the rules carry some ... -
Adoption of IP truncation in a privacy-based decision tree pruning design: A case study in network intrusion detection system
(2022-03-04)A decision tree is a transparent model where the rules are visible and can represent the logic of classification. However, this structure might allow attackers to infer confidential information if the rules carry some ... -
Asymmetric hashing for fast ranking via neural network measures
(2022-11-01)Fast item ranking is an important task in recommender systems. In previous works, graph-based Approximate Nearest Neighbor (ANN) approaches have demonstrated good performance on item ranking tasks with generic searching/matching ... -
Asymmetric hashing for fast ranking via neural network measures
(2022-11)Fast item ranking is an important task in recommender systems. In previous works, graph-based Approximate Nearest Neighbor (ANN) approaches have demonstrated good performance on item ranking tasks with generic searching/matching ... -
AUC Maximization for Low-Resource Named Entity Recognition
(2023-04-13)Current work in named entity recognition (NER) uses either cross entropy (CE) or conditional random fields (CRF) as the objective/loss functions to optimize the underlying NER model. Both of these traditional objective ... -
Bayesian estimate of mean proper scores for diversity-enhanced active learning
(2023-12-15)The effectiveness of active learning largely depends on the sampling efficiency of the acquisition function. Expected Loss Reduction (ELR) focuses on a Bayesian estimate of the reduction in classification error, and more ... -
Benchmarking full version of GureKDDCup, UNSW-NB15, and CIDDS-001 NIDS datasets using rolling-origin resampling
(2021-10)Network intrusion detection system (NIDS) is a system that analyses network traffic to flag malicious traffic or suspicious activities. Several recent NIDS datasets have been published, however, the lack of baseline ... -
Benchmarking saliency methods for chest X-ray interpretation
(2022-08)Saliency methods, which produce heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making. However, rigorous investigation ... -
Benchmarking saliency methods for chest X-ray interpretation
(2022-10)Saliency methods, which produce heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making. However, rigorous investigation ... -
CapNext: Unifying Capsule and ResNeXt for Medical Image Segmentation
(2022)Capsule Network is a contemporary approach to image analysis that emphasizes part-whole relationships. However, its applications to segmentation tasks are limited due to training difficulties such as initialization and ... -
Clearing payments in dynamic financial networks
(2023-12)This paper proposes a novel dynamical model for determining clearing payments in financial networks. We extend the classical Eisenberg–Noe model of financial contagion to multiple time periods, allowing financial operations ... -
Coexistence of surface lattice resonances and bound states in the continuum in a plasmonic lattice
(2022-03-14)We present a numerical study on a 2D array of plasmonic structures covered by a subwavelength film. We explain the origin of surface lattice resonances (SLRs) using the coupled dipole approximation and show that the ... -
Collaborative Curating for Discovery and Expansion of Visual Clusters
(2021-10)In many visually-oriented applications, users can select and group images that they find interesting into coherent clusters. For instance, we encounter these in the form of hashtags on Instagram, galleries on Flickr, or ... -
ColorRL: Reinforced Coloring for End-to-End Instance Segmentation
(2021)Instance segmentation, the task of identifying and separating each individual object of interest in the image, is one of the actively studied research topics in computer vision. Although many feed-forward networks produce ...
