Search Results for author:
Found 26 papers, 8 papers with code
Full-Time Monocular Road Detection Using Zero-Distribution Prior of Angle of Polarization
Zero-distribution prior embodies the zero-distribution of Angle of Polarization (AoP) of a road scene image, which provides a significant contrast between the road and the background.
Corner Detection Based on Multi-directional Gabor Filters with Multi-scales
In this work, the capability of the Gabor function to discriminate the intensity changes of step edges, L-shaped corners, Y-shaped or T-shaped corners, X-shaped corners, and star-shaped corners are investigated.
UMIFormer: Mining the Correlations between Similar Tokens for Multi-View 3D Reconstruction
We empirically demonstrate on ShapeNet and confirm that our decoupled learning method is adaptable for unordered multiple images.
An Adaptive Plug-and-Play Network for Few-Shot Learning
Few-shot learning (FSL) requires a model to classify new samples after learning from only a few samples.
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
Analog in-memory computing (AIMC) -- a promising approach for energy-efficient acceleration of deep learning workloads -- computes matrix-vector multiplications (MVMs) but only approximately, due to nonidealities that often are non-deterministic or nonlinear.
Short-time SSVEP data extension by a novel generative adversarial networks based framework
TEGAN transforms short-time SSVEP signals into long-time artificial SSVEP signals.
Multimodal Remote Sensing Image Registration Based on Adaptive Multi-scale PIIFD
Therefore, this paper proposes a multimodal remote sensing image registration method based on adaptive multi-scale PIIFD(AM-PIIFD).
GARNet: Global-Aware Multi-View 3D Reconstruction Network and the Cost-Performance Tradeoff
Deep learning technology has made great progress in multi-view 3D reconstruction tasks.
Lexical semantics enhanced neural word embeddings
To improve vector space models in deriving semantic similarity, we post-process neural word embeddings through deep metric learning, through which we can inject lexical-semantic relations, including syn/antonymy and hypo/hypernymy, into a distributional space.
Synonym Detection Using Syntactic Dependency And Neural Embeddings
By comparing various Vector Space Models in detecting synonyms in TOEFL, we systematically study the salience of syntactic dependencies in accounting for distributional similarity.
In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit Memory
We demonstrate for the first time how the EM unit can physically superpose multiple training examples, expand to accommodate unseen classes, and perform similarity search during inference, using operations on an IMC core based on phase-change memory (PCM).
Constructing Trajectory and Predicting Estimated Time of Arrival for Long Distance Travelling Vessels: A Probability Density-based Scanning Approach
In this study, a probability density-based approach for constructing trajectories is proposed and validated through an typical use-case application: Estimated Time of Arrival (ETA) prediction given origin-destination pairs.
Optimizing Coordinative Schedules for Tanker Terminals: An Intelligent Large Spatial-Temporal Data-Driven Approach -- Part 2
In this study, a novel coordinative scheduling optimization approach is proposed to enhance port efficiency by reducing weighted average turnaround time.
Optimizing Coordinative Schedules for Tanker Terminals: An Intelligent Large Spatial-Temporal Data-Driven Approach -- Part 1
In this study, a novel coordinative scheduling optimization approach is proposed to enhance port efficiency by reducing average wait time and turnaround time.
Real-time division-of-focal-plane polarization imaging system with progressive networks
Division-of-focal-plane (DoFP) polarization imaging technical recently has been applied in many fields.
Anomaly Detection via Self-organizing Map
Anomaly detection plays a key role in industrial manufacturing for product quality control.
Ranked #21 on
Anomaly Detection
on MVTec AD
A Benchmark of Ocular Disease Intelligent Recognition: One Shot for Multi-disease Detection
In ophthalmology, early fundus screening is an economic and effective way to prevent blindness caused by ophthalmic diseases.
Multimodal Gait Recognition for Neurodegenerative Diseases
In recent years, single modality based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognised that each of the established approaches has different strengths and weaknesses.
SeqGenSQL -- A Robust Sequence Generation Model for Structured Query Language
We explore using T5 (Raffel et al. (2019)) to directly translate natural language questions into SQL statements.
SWIPENET: Object detection in noisy underwater images
Moreover, inspired by the human education process that drives the learning from easy to hard concepts, we here propose the CMA training paradigm that first trains a clean detector which is free from the influence of noisy data.
Bridging the gap between photovoltaics R&D and manufacturing with data-driven optimization
Novel photovoltaics, such as perovskites and perovskite-inspired materials, have shown great promise due to high efficiency and potentially low manufacturing cost.
Applied Physics
The Prevalence of Errors in Machine Learning Experiments
Objective: We investigate the incidence of errors in a sample of machine learning experiments in the domain of software defect prediction.
Deep Learning-based Radiomic Features for Improving Neoadjuvant Chemoradiation Response Prediction in Locally Advanced Rectal Cancer
The model built with handcrafted features achieved the mean area under the ROC curve (AUC) of 0. 64, while the one built with DL-based features yielded the mean AUC of 0. 73.
Deep Neural Net with Attention for Multi-channel Multi-touch Attribution
Customers are usually exposed to online digital advertisement channels, such as email marketing, display advertising, paid search engine marketing, along their way to purchase or subscribe products( aka.
Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval
In addition, we harness a self-supervised semantic network to discover high-level semantic information in the form of multi-label annotations.
Detection and Attention: Diagnosing Pulmonary Lung Cancer from CT by Imitating Physicians
This paper proposes a novel and efficient method to build a Computer-Aided Diagnoses (CAD) system for lung nodule detection based on Computed Tomography (CT).
