Results 21 to 30 of about 7,628 (169)
IEEE Transactions on Neural Networks and Learning Systems, 2018 Although hash function learning algorithms have achieved great success in recent years, most existing hash models are off-line, which are not suitable for processing sequential or online data. To address this problem, this work proposes an online hash model to accommodate data coming in stream for online learning.
Long-Kai Huang +2 more
openaire +4 more sources
On the Design of a Blockchain-based Fraud-prevention Performance Appraisal System
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2022 The job recruitment process takes a lot of process and number of documents. It is very well known for applicants to exaggerated and falsify their work history data. It may put a company at legal risk and significant commercial losses.
Bryan Andi Gerrardo +2 more
doaj +1 more source
Machine Learning, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cong Leng, Jian Cheng 0001
openaire +2 more sources
Deep Hashing Based on Class-Discriminated Neighborhood Embedding
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Deep-hashing methods have drawn significant attention during the past years in the field of remote sensing (RS) owing to their prominent capabilities for capturing the semantics from complex RS scenes and generating the associated hash codes in an end-to-
Jian Kang +4 more
doaj +1 more source
Theoretical Computer Science, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Czech, Zbigniew J. +2 more
openaire +5 more sources
Scalable IoT Platform for Heterogeneous Devices in Smart Environments
IEEE Access, 2020 The Internet of Things (IoT) is envisioned as a ubiquitous computing infrastructure in which everything becomes connected, enabling gigantic information exchange among Things and people.
Asad Javed +3 more
doaj +1 more source
International Journal of Approximate Reasoning, 2009 AbstractWe show how to learn a deep graphical model of the word-count vectors obtained from a large set of documents. The values of the latent variables in the deepest layer are easy to infer and give a much better representation of each document than Latent Semantic Analysis.
Ruslan Salakhutdinov, Geoffrey E. Hinton
openaire +1 more source
CoRR, 2021 This paper proposes a novel ternary hash encoding for learning to hash methods, which provides a principled more efficient coding scheme with performances better than those of the state-of-the-art binary hashing counterparts. Two kinds of axiomatic ternary logic, Kleene logic and Łukasiewicz logic are adopted to calculate the Ternary Hamming Distance ...
Chang Liu 0069 +7 more
openaire +2 more sources
Distributed Fast Supervised Discrete Hashing
IEEE Access, 2019 Hash-based learning has attracted considerable attention due to its fast retrieval speed and low computational cost for the large-scale database. Compared with unsupervised hashing, supervised hashing achieves higher retrieval accuracy generally by ...
Zhifeng Liu, Feng Chen, Shukai Duan
doaj +1 more source