Digital Library
Search: "[ keyword: Deep Learning ]" (65)
Deep Learning Description Language for Referring to Analysis Model Based on Trusted Deep Learning
Jong Hyeok Mun, Do Hyung Kim, Jong Sun Choi, Jae Young Choi KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 4, pp. 133-142,
Apr.
2021
https://doi.org/10.3745/KTSDE.2021.10.4.133
Keywords: Trusted Deep Learning, Model Reference, Deep Learning Description Language, Traffic Situation Analysis Model
https://doi.org/10.3745/KTSDE.2021.10.4.133
Keywords: Trusted Deep Learning, Model Reference, Deep Learning Description Language, Traffic Situation Analysis Model
1D CNN and Machine Learning Methods for Fall Detection
Inkyung Kim, Daehee Kim, Song Noh, Jaekoo Lee KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 3, pp. 85-90,
Mar.
2021
https://doi.org/10.3745/KTSDE.2021.10.3.85
Keywords: Machine Learning, Deep Learning, Fall Detection, 1D Convolutional Neural Network
https://doi.org/10.3745/KTSDE.2021.10.3.85
Keywords: Machine Learning, Deep Learning, Fall Detection, 1D Convolutional Neural Network
Hangul Font Dataset for Korean Font Research Based on Deep Learning
Debbie Honghee Ko, Hyunsoo Lee, Jungjae Suk, Ammar Ul Hassan, Jaeyoung Choi KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 2, pp. 73-78,
Feb.
2021
https://doi.org/10.3745/KTSDE.2021.10.2.73
Keywords: Deep Learning, Font Data, Automatic Font Generation, Hangul Font Dataset, Hangul Font
https://doi.org/10.3745/KTSDE.2021.10.2.73
Keywords: Deep Learning, Font Data, Automatic Font Generation, Hangul Font Dataset, Hangul Font
Improved Network Intrusion Detection Model through Hybrid Feature Selection and Data Balancing
Byeongjun Min, Jihun Ryu, Dongkyoo Shin, Dongil Shin KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 2, pp. 65-72,
Feb.
2021
https://doi.org/10.3745/KTSDE.2021.10.2.65
Keywords: Intrusion Dectection, Deep Learning, Over Sampling, Feature selection
https://doi.org/10.3745/KTSDE.2021.10.2.65
Keywords: Intrusion Dectection, Deep Learning, Over Sampling, Feature selection
Double Encoder-Decoder Model for Improving the Accuracy of the Electricity Consumption Prediction in Manufacturing
Yeongchang Cho, Byung Gill Go, Jong Hoon Sung, Yeong Sik Cho KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 12, pp. 419-430,
Dec.
2020
https://doi.org/10.3745/KTSDE.2020.9.12.419
Keywords: Time-Series Forecasting, Deep Learning, Machine Learning
https://doi.org/10.3745/KTSDE.2020.9.12.419
Keywords: Time-Series Forecasting, Deep Learning, Machine Learning
Real Time Face detection Method Using TensorRT and SSD
Hye-Bin Yoo, Myeong-Suk Park, Sang-Hoon Kim KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 10, pp. 323-328,
Oct.
2020
https://doi.org/10.3745/KTSDE.2020.9.10.323
Keywords: Tensorflow, TensorRT, Deep Learning, SSD, Object Detection
https://doi.org/10.3745/KTSDE.2020.9.10.323
Keywords: Tensorflow, TensorRT, Deep Learning, SSD, Object Detection
Mortality Prediction of Older Adults Using Random Forest and Deep Learning
Junhyeok Park, Songwook Lee KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 10, pp. 309-316,
Oct.
2020
https://doi.org/10.3745/KTSDE.2020.9.10.309
Keywords: Mortality Prediction, Convolutional Neural Network, Random Forest, Feature selection, Deep Learning
https://doi.org/10.3745/KTSDE.2020.9.10.309
Keywords: Mortality Prediction, Convolutional Neural Network, Random Forest, Feature selection, Deep Learning
An Efficient Deep Learning Based Image Recognition Service System Using AWS Lambda Serverless Computing Technology
Hyunchul Lee, Sungmin Lee, Kangseok Kim KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 6, pp. 177-186,
Jun.
2020
https://doi.org/10.3745/KTSDE.2020.9.6.177
Keywords: Deep Learning, Serverless Computing, AWS Lambda Server, Cold Start Time, capacity limitation
https://doi.org/10.3745/KTSDE.2020.9.6.177
Keywords: Deep Learning, Serverless Computing, AWS Lambda Server, Cold Start Time, capacity limitation
Topic Analysis of the National Petition Site and Prediction of Answerable Petitions Based on Deep Learning
Woo Yun Hui, Hyon Hee Kim KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 2, pp. 45-52,
Feb.
2020
https://doi.org/10.3745/KTSDE.2020.9.2.45
Keywords: National Petition, Topic Analysis, topic modeling, K-Means Clustering, LSTM, Deep Learning
https://doi.org/10.3745/KTSDE.2020.9.2.45
Keywords: National Petition, Topic Analysis, topic modeling, K-Means Clustering, LSTM, Deep Learning
Measurement of Construction Material Quantity through Analyzing Images Acquired by Drone And Data Augmentation
Ji-Hwan Moon, Nu-Lee Song, Jae-Gab Choi, Jin-Ho Park, Gye-Young Kim KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 1, pp. 33-38,
Jan.
2020
https://doi.org/10.3745/KTSDE.2020.9.1.33
Keywords: Drone, UAV, RCNN, Deep Learning, Counting Number, Construction Material
https://doi.org/10.3745/KTSDE.2020.9.1.33
Keywords: Drone, UAV, RCNN, Deep Learning, Counting Number, Construction Material
Indexing
All publications of KTSDE is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.
KTSDE is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).
