Publication

SCI(E) Journal Papers (Published/Accepted)

1. Abdul Rehman, Faisal Saeed, Muhammad Mazhar Ullah Rathore, Anand Paul, and Jae-Mo Kang, “Smart City Fire Surveillance: A Deep State-Space Model with Intelligent Agents,” IET Smart Cities, accepted for publication, Jun. 2024.

2. Jae-Mo Kang, “RobuT-Net: Dual CNN-Based Robust Training Sequence Design for IoT Systems,” IEEE Internet of Things Journal, vol. 11, no. 10, pp. 18930–18931, May 2024.

3. Chae Yoon Jung, Jae Mo Kang, and Dong In Kim, “A Channel Estimation Method Using Denoising Autoencoder for Large-Scale Asymmetric Backscatter Systems,” ICT Express, vol. 10, no. 2, pp. 400–405, Apr. 2024.

4. Jae-Mo Kang, “A Novel Training Design Algorithm for Kronecker-Inseparable MIMO Systems With General Power Constraints,” IEEE Transactions on Vehicular Technology, accepted for publication, Apr. 2024.

5. Vikas Palakonda, Jae-Mo Kang, and Heechul Jung, “Clustering-aided Grid-Based One-to-One Selection-driven Evolutionary Algorithm for Multi/Many-objective Optimization,” IEEE Access, accepted for publication, May 2024.

6. Jae-Mo Kang, “Deep Learning Enabled Multicast Beamforming With Movable Antenna Array,” IEEE Wireless Communications Letters, accepted for publication, Apr. 2024.

7. Jamshid Tursunboev, Vikas Palakonda, and Jae-Mo Kang, “Multi-Objective Evolutionary Hybrid Deep Learning for Energy Theft Detection,” Applied Energy, vol. 363, pp. 122847, Jun. 2024.

8. Chae-Won Park, Vikas Palakonda, Sangseok Yun, Il-Min Kim, and Jae-Mo Kang, “OCR-Diff: A Two-Stage Deep Learning Framework for Optical Character Recognition Using Diffusion Model in Industrial Internet-of-Things,” IEEE Internet of Things Journal, accepted for publication, Apr. 2024.

9. Vikas Palakonda, Jae-Mo Kang, and Heechul Jung, “Benchmarking Real-World Many-Objective Problems: A Problem Suite With Baseline Results,” IEEE Access, vol. 12, pp. 49275–49290, Apr. 2024.

10. Jae-Mo Kang and Dong-Woo Lim, “Joint Channel Training and Passive Beamforming Design for Intelligent Reflecting Surface-Aided LoRa Systems,” AIMS Mathematics, vol. 9, no. 5, pp. 11423–11431, Mar. 2024.

11. Jae-Mo Kang, “Deep-Learning-Based Robust Channel Estimation for MIMO IoT Systems,” IEEE Internet of Things Journal, vol. 11, no. 6, pp. 9882–9895, Mar. 2024.

12. Jae-Mo Kang and Dong-Woo Lim, “Robust Transceiver Design for Correlated MIMO Interference Channels in the Presence of CSI Errors under General Power Constraints,” Mathematics, vol. 12, no. 6, pp. 801, Mar. 2024.

13. Jae-Mo Kang and Dong-Woo Lim, “Corrections to “On the Quasi-Orthogonality of LoRa Modulation”,” IEEE Internet of Things Journal, vol. 11, no. 5, pp. 9229, Mar. 2024.

14. Jae-Mo Kang, “Corrections to “LoRa Preamble Detection with Optimized Thresholds”,” IEEE Internet of Things Journal, vol. 11, no. 5, pp. 9228, Mar. 2024.

15. Jae-Mo Kang, Dong-Woo Lim, and Kyu-Min Kang, “Corrections to “On the LoRa Modulation for IoT: Optimal Preamble Detection and Its Performance Analysis”,” IEEE Internet of Things Journal, vol. 11, no. 5, pp. 9227, Mar. 2024.

16. Jae-Mo Kang, “Corrections to “MIMO-LoRa for High-Data-Rate IoT: Concept and Precoding Design”,” IEEE Internet of Things Journal, vol. 11, no. 5, pp. 9226, Mar. 2024.

17. Jae-Mo Kang, “On the LoRa Modulation for IoT: Preamble Designs for Channel Estimation With Single- and Multi-Chirp Transmission Strategies,” IEEE Internet of Things Journal, accepted for publication, Feb. 2024.

18. Yosoeb Shin, Vikas Palakonda, Sangseok Yun, Il-Min Kim, Seon-Gon Kim, Sang-Mi Park, and Jae-Mo Kang, “RandMixAugment: A Novel Unified Technique for Region- and Image-Level Data Augmentations,” IEEE Access, vol. 12, pp. 8187–8197, Jan. 2024.

19. Jae-Mo Kang and Kae Won Choi, “Efficient Demodulation Algorithms for MIMO-LoRa,” IEEE Internet of Things Journal, vol. 10, no. 23, pp. 21129–21130, Dec. 2023.

20. Vikas Palakonda and Jae-Mo Kang, “Erratum to “Pre-DEMO: Preference-Inspired Differential Evolution for Multi/Many-Objective Optimization”,” IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 53, no. 12, pp. 7902, Dec. 2023.

21. Vikas Palakonda and Jae-Mo Kang, “Pre-DEMO: Preference-Inspired Differential Evolution for Multi/Many-Objective Optimization,” IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 53, no. 12, pp. 7618–7630, Dec. 2023.

22. Azadeh Motamedi, Sangseok Yun, Jae-Mo Kang, Yiqun Ge, and Il-Min Kim, “Redundancy Management in Federated Learning for Fast Communication,” IEEE Transactions on Communications, vol. 71, no. 11, pp. 6332–6347, Nov. 2023.

23. Hyeon-Uk Lee, Chang-Jae Chun, and Jae-Mo Kang, “Causality-Driven Efficient Feature Selection for Deep Learning-Based Surface Roughness Prediction in Milling Machines,” Mathematics, vol. 11, no. 22, pp. 4682, Sep. 2023.

24. Jae-Mo Kang, “Corrections to “Intelligent Reflecting Surface: Joint Optimal Training Sequence and Refection Pattern”,” IEEE Communications Letters, vol. 27, no. 11, pp. 3142, Nov. 2023.

25. Vikas Palakonda and Jae-Mo Kang, “Many-Objective Real-World Engineering Problems: A Comparative Study of State-of-the-Art Algorithms,” IEEE Access, vol. 11, pp. 111636–111654, Oct. 2023.

26. Hasnain Ali Shah and Jae-Mo Kang, “An Optimized Multi-Organ Cancer Cells Segmentation for Histopathological Images Based on CBAM-Residual U-Net,” IEEE Access, vol. 11, pp. 111608–111621, Oct. 2023.

27. Seong-Hwan Kang, Vikas Palakonda, Il-Min Kim, Jae-Mo Kang, and Sangseok Yun, “Enhanced Non-Maximum Suppression for the Detection of Steel Surface Defects,” Mathematics, vol. 11, no. 18, pp. 3898, Sep. 2023.

28. Hasnain Ali Shah, Faisal Saeed, Muhammad Diyan, Nouf Abdullah Almujally, and Jae-Mo Kang, “ECG-TransCovNet: A Hybrid Transformer Model for Accurate Arrhythmia Detection using ECG Signals,” CAAI Transactions on Intelligence Technology, accepted for publication, Sep. 2023.

29. Vikas Palakonda, Jae-Mo Kang, and Heechul Jung, “An Effective Ensemble Framework for Many-Objective Optimization based on AdaBoost and K-means Clustering,” Expert Systems With Applications, vol. 227, pp. 120278, Oct. 2023.

30. Jae-Mo Kang and Dong-Woo Lim, “On the Quasi-Orthogonality of LoRa Modulation,” IEEE Internet of Things Journal, vol. 10, no. 14, pp. 12366–12378, Jul. 2023.

31. Jae-Mo Kang, “A New Index Modulation for LoRa,” IEEE Internet of Things Journal, vol. 10, no. 13, pp. 11938–11939, Jul. 2023.

32. Jae-Mo Kang, “LoRa Preamble Detection with Optimized Thresholds,” IEEE Internet of Things Journal, vol. 10, no. 7, pp. 6525–6526, Apr. 2023.

33. Mingyu Sung, Jaesoo Kim, and Jae-Mo Kang, “Probabilistic Classification Method of Spiking Neural Network Based on Multi-Labeling of Neurons,” Mathematics, vol. 11, no. 5, pp. 1224, Mar. 2023.

34. Byungjo Kim and Jae-Mo Kang, “User Grouping, Precoding Design, and Power Allocation for MIMO-NOMA Systems,” Mathematics, vol. 11, no. 4, pp. 995, Feb. 2023.

35. Jae-Mo Kang and Sunghwan Moon, “Error Bounds for ReLU Networks With Depth and Width Parameters," Japan Journal of Industrial and Applied Mathematics, vol. 40, no. 1, pp. 275–288, Jan. 2023.

36. Dong-Woo Lim, Chang-Jae Chun, and Jae-Mo Kang, “Transmit Power Adaptation for D2D Communications Underlaying SWIPT-based IoT Cellular Networks,” IEEE Internet of Things Journal, vol. 10, no. 2, pp. 987–1000, Jan. 2023.

37. Damar Novtahaning, Hasnain Ali Shah, and Jae-Mo Kang, “Deep Learning Ensemble-Based Automated and High-Performing Recognition of Coffee Leaf Disease,” Agriculture, vol. 12, no. 11, pp. 1909–1924, Nov. 2022. 

38. Arif Ullah, Ziaul Haq Abbas, Ghulam Abbas, Fazal Muhammad, and Jae-Mo Kang, “Hybrid millimeter wave heterogeneous networks with spatially correlated user equipment,” Digital Communications and Networks, accepted for publication, Oct. 2022.

39. Sijia Li, Furkat Sultonov, Jamshid Tursunboev, Jun-Hyun Park, Sangseok Yun, and Jae-Mo Kang, “Ghostformer: A GhostNet-based Two-stage Transformer for Small Object Detection,” Sensors, vol. 22, no. 18, pp. 6939, Sep. 2022.

40. Hasnain Ali Shah, Faisal Saeed, Sangseok Yun, Jun-Hyun Park, Anand Paul, and Jae-Mo Kang, “A Robust Approach for Brain Tumor Detection in Magnetic Resonance Images Using Finetuned EfficientNet,” IEEE Access, vol. 10, pp. 65426–65438, Jun. 2022.

41. Sijia Li, Furkat Sultonov, Qingshan Ye, Yong Bai, Jun-Hyun Park, Chilsig Yang, Minseok Song, Sungwoo Koo, and Jae-Mo Kang, “TA-Unet: Integrating Triplet Attention Module for Drivable Road Region Segmentation,” Sensors, vol. 22, no. 12, pp. 4438, Jun. 2022.

42. Vikas Palakonda, Jae-Mo Kang, and Heechul Jung, “An Adaptive Neighborhood based Evolutionary Algorithm with Pivot-Solution based Selection for Multi- and Many-Objective Optimization,” Information Sciences, vol. 607, pp. 126–152, Aug. 2022.

43. Jae-Mo Kang, “MIMO-LoRa for High-Data-Rate IoT: Concept and Precoding Design,” IEEE Internet of Things Journal, vol. 9, no. 12, pp. 10368–10369, Jun. 2022. 

44. Yeong-Rok Kim, Jun-Hyun Park, Jae-Mo Kang, Dong-Woo Lim, and Kyu-Min Kang, “Deep Learning-Aided Downlink Beamforming Design and Uplink Power Allocation for UAV Wireless Communications with LoRa,” Applied Sciences, vol. 12, no. 10, pp. 4826, May 2022.

45. Jae-Mo Kang, Dong-Woo Lim, and Kyu-Min Kang, “On the LoRa Modulation for IoT: Optimal Preamble Detection and Its Performance Analysis,” IEEE Internet of Things Journal, vol. 9, no. 7, pp. 4973–4986, Apr. 2022. 

46. Jae-Mo Kang, Sangseok Yun, Il-Min Kim, and Heechul Jung, “MSE-Based Joint Transceiver and Passive Beamforming Designs for Intelligent Reflecting Surface-Aided MIMO Systems,” IEEE Wireless Communications Letters, vol. 11, no. 3, pp. 622–626, Mar. 2022. 

47. Jacob Mathias Nilsen, Jun-Hyun Park, Sangseok Yun, Jae-Mo Kang, and Heechul Jung, “Competing Miners: A Synergetic Solution for Combining Blockchain and Edge Computing in Unmanned Aerial Vehicle Networks,” Applied Sciences, vol. 12, no. 5, pp. 2581, Mar. 2022.

48. Furkat Sultonov, Jun-Hyun Park, Sangseok Yun, Dong-Woo Lim, and Jae-Mo Kang, “Mixer U-Net: An Improved Automatic Road Extraction from UAV Imagery,” Applied Sciences, vol. 12, no. 4, pp. 1953, Feb. 2022.

49. Sangseok Yun, Jae-Mo Kang, Jeongseok Ha, Sangho Lee, Dong-Woo Ryu, Jihoe Kwon, and Il-Min Kim, “Deep Learning-based Ground Vibration Monitoring: Reinforcement Learning and RNN-CNN Approach,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1–5, Jan. 2022. 

50. Jamshid Tursunboev, Yong-Sung Kang, Sung-Bum Huh, Dong-Woo Lim, Jae-Mo Kang, Heechul Jung, “Hierarchical Federated Learning for Edge-Aided Unmanned Aerial Vehicle Networks,” Applied Sciences, vol. 12, no. 2, pp. 670, Jan. 2022.

51. Sangseok Yun, Jae-Mo Kang, Sooyong Choi, and Il-Min Kim, “Cooperative Inference of DNNs over Noisy Wireless Channels,” IEEE Transactions on Vehicular Technology, vol. 70, no. 8, pp. 8298–8303, Aug. 2021.

52. Byungjo Kim, Jae-Mo Kang, Hyung-Myung Kim, and Joonhyuk Kang, “Joint Channel Estimation, Training Design, Tx Power Allocation, and Rx Power Splitting for MIMO SWIPT Systems,” IEEE Communications Letters, vol. 25, no. 4, pp. 1269–1273, Apr. 2021.

53. Jae-Mo Kang, Chang-Jae Chun, Il-Min Kim, and Dong In Kim, “Deep RNN-Based Channel Tracking for Wireless Energy Transfer System,” IEEE Systems Journal, vol. 14, no. 3, pp. 4340–4343, Sep. 2020.

54. Jae-Mo Kang and Chang-Jae Chun, “Joint Trajectory Design, Tx Power Allocation, and Rx Power Splitting for UAV-Enabled Multicasting SWIPT Systems,” IEEE Systems Journal, vol. 14, no. 3, pp. 3740–3743, Sep. 2020. 

55. Jae-Mo Kang, Il-Min Kim, and Chang-Jae Chun, “Deep Learning-Based MIMO-NOMA with Imperfect SIC Decoding,” IEEE Systems Journal, vol. 14, no. 3, pp. 3414–3417, Sep. 2020.

56. Jae-Mo Kang, “Intelligent Reflecting Surface: Joint Optimal Training Sequence and Refection Pattern,” IEEE Communications Letters, vol. 24, no. 8, pp. 1784–1788, Aug. 2020.

57. Jae-Mo Kang, “Reinforcement Learning Based Adaptive Resource Allocation for Wireless Powered Communication Systems,” IEEE Communications Letters, vol. 24, no. 8, pp. 1752–1756, Aug. 2020.

58. Jae-Mo Kang, Chang-Jae Chun, and Il-Min Kim, “Deep Learning Based Channel Estimation for MIMO Systems with Received SNR Feedback,” IEEE Access, vol. 8, pp. 121162–121181, Jul. 2020.  

59. Jae-Mo Kang, Chang-Jae Chun, Il-Min Kim, and Dong In Kim, “Dynamic Power Splitting for SWIPT with Nonlinear Energy Harvesting in Ergodic Fading Channel,” IEEE Internet of Things Journal, vol. 7, no. 6, pp. 5648–5665, Jun. 2020.  

60. Chang-Jae Chun and Jae-Mo Kang, “Optimal Training Design for MIMO Amplify-and-Forward Two-Way Relay Systems in the Presence of Interference,” vol. 69, no. 5, pp. 5151–5163, IEEE Transactions on Vehicular Technology, May 2020. 

61. Sangseok Yun, Jae-Mo Kang, Il-Min Kim, and Jeongseok Ha, “Deep Artificial Noise: Deep Learning-Based Precoding Optimization for Artificial Noise Scheme,” IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 3465–3469, Mar. 2020. 

62. Jae-Mo Kang, Il-Min Kim, Sangho Lee, Dong-Woo Ryu, and Jihoe Kwon, “A Deep CNN Based Ground Vibration Monitoring Scheme for MEMS Sensed Data,” IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 2, pp. 347–351, Feb. 2020. 

63. Chang-Jae Chun, Jae-Mo Kang, and Il-Min Kim, “Deep Learning-Based Joint Pilot Design and Channel Estimation for Multiuser MIMO Channels,” IEEE Communications Letters, vol. 23, no. 11, pp. 1999–2003, Nov. 2019.

64. Chang-Jae Chun, Jae-Mo Kang, and Il-Min Kim, “Deep Learning Based Channel Estimation for Massive MIMO Systems,” IEEE Wireless Communications Letters, vol. 8, no. 4, pp. 1228–1231, Aug. 2019.

65. Jae-Mo Kang, Il-Min Kim, and Dong In Kim, “Joint Tx Power Allocation and Rx Power Splitting for SWIPT system with Multiple Nonlinear Energy Harvesting Circuits,” IEEE Wireless Communications Letters, vol. 8, no. 1, pp. 53–56, Feb. 2019.

66. Chang-Jae Chun, Jae-Mo Kang, and Il-Min Kim, “Adaptive Rate and Energy Harvesting Interval Control Based on Reinforcement Learning for SWIPT,” IEEE Communications Letters, vol. 22, no. 12, pp. 2571–2574, Dec. 2018. 

67. Jae-Mo Kang, Chang-Jae Chun, and Il-Min Kim, “Deep-Learning-Based Channel Estimation for Wireless Energy Transfer,” IEEE Communications Letters, vol. 22, no. 11, pp. 2310–2313, Nov. 2018.

68. Jae-Mo Kang and Il-Min Kim, “Optimal User Grouping for Downlink NOMA,” IEEE Wireless Communications Letters, vol. 7, no. 5, pp. 724–727, Oct. 2018.

69. Xinghua Jia, Chaozhu Zhang, Jae-Mo Kang, and Il-Min Kim, “Joint Beamforming Design and Time Allocation for Wireless Powered Asymmetric Two-Way Multirelay Network,” IEEE Transactions on Vehicular Technology, vol. 67, no. 10, pp. 9641–9655, Oct. 2018.

70. Jae-Mo Kang, Il-Min Kim, and Hyung-Myung Kim, “Estimation of Time-Varying Channels in MIMO Two-Way Multi-Relay Systems,” IEEE Transactions on Wireless Communications, vol. 17, no. 6, pp. 4002–4016, Jun. 2018.

71. Jae-Mo Kang, Il-Min Kim, and Dong In Kim, “Joint Optimal Mode Switching and Power Adaptation for Nonlinear Energy Harvesting SWIPT System over Fading Channel,” IEEE Transactions on Communications, vol. 66, no. 4, pp. 1817–1832, Apr. 2018. 

72. Jae-Mo Kang, Il-Min Kim, and Dong In Kim, “Wireless Information and Power Transfer: Rate-Energy Tradeoff for Nonlinear Energy Harvesting,” IEEE Transactions on Wireless Communications, vol. 17, no. 3, pp. 1966–1981, Mar. 2018.

73. Il-Min Kim, Dong In Kim, and Jae-Mo Kang, “Rate-Energy Tradeoff and Decoding Error Probability-Energy Tradeoff for SWIPT in Finite Codelength,” IEEE Transactions on Wireless Communications, vol. 16, no. 12, pp. 8220–8234, Dec. 2017. 

74. Jae-Mo Kang, Jun Yang, Jeongseok Ha, and Il-Min Kim, “Joint Design of Optimal Precoding and Cooperative Jamming for Multiuser Secure Broadcast Systems,” IEEE Transactions on Vehicular Technology, vol. 66, no. 11, pp. 10551–10556, Nov. 2017. 

75. Jae-Mo Kang, Il-Min Kim, and Dong In Kim, “Mode Switching for SWIPT over Fading Channel with Nonlinear Energy Harvesting,” IEEE Wireless Communications Letters, vol. 6, no. 5, pp. 678–681, Oct. 2017.

76. Jae-Mo Kang, Il-Min Kim, and Hyung-Myung Kim, “Optimal Training Design for MIMO-OFDM Two-Way Relay Networks,” IEEE Transactions on Communications, vol. 65, no. 9, pp. 3675–3690, Sep. 2017. 

77. Jae-Mo Kang and Hyung-Myung Kim, “Training Designs for Estimation of Spatially Correlated Fading Channels in MIMO Amplify-and-Forward Two-Way Multi-Relay Networks,” IEEE Communications Letters, vol. 20, no. 4, pp. 772–775, Apr. 2016. 

78. Jae-Mo Kang and Hyung-Myung Kim, “Both Minimum MSE and Maximum SNR Channel Training Designs for MIMO AF Multi-Relay Networks with Spatially Correlated Fading,” IEEE Signal Processing Letters, vol. 18, no. 3, pp. 1888–1892, Nov. 2015. 

Domestic Journal Papers (Published/Accepted)

1. 최병준, 윤상석, 이세훈, 강재모, "분할 연산 기반 순환 신경망의 추론 성능 분석," 한국지능시스템학회 논문지, 제33권, 제1호, 37쪽–44쪽, 2023년 2월.
   Byeong-Jun Choi, Sangseok Yun, Se-Hun Lee, and Jae-Mo Kang, "Analysis on Inference Latency of Recurrent Neural Networks with Split Computing," Journal of Korean Institute of Intelligent Systems, vol. 33, no. 1, pp. 37–44, Feb. 2023.

2. 강성환, 신요섭, 이세훈, 박준현, 강재모, "Exponential NMS : 금속 외관의 오탐 성능 개선을 위한 효과적인 바운딩 박스 중첩 억제 기법," 한국지능시스템학회 논문지, 제32권, 제6호, 464쪽–472쪽, 2022년 12월.
   Seong-Hwan Kang, Yo-Seob Shin, Se-Hun Lee, Jun-Hyun Park, and Jae-Mo Kang, "Exponential NMS : A New NMS Method for Suppression of Overlapped Bounding Box in Detection of Steel Surface Defects," Journal of Korean Institute of Intelligent Systems, vol. 32, no. 6, pp. 464–472, Dec. 2022.

3. 이동훈, 이세훈, 강재모, "신제품 개발을 위한 GAN 기반 생성모델 성능 비교," 문화기술의 융합, 제8권, 제6호, 867쪽–871쪽, 2022년 11월.
   Dong-Hun Lee, Se-Hun Lee, and Jae-Mo Kang, "Performance Comparisons of GAN-Based Generative Models for New Product Development," The Journal of the Convergence on Culture Technology, vol. 8, no. 6, pp. 867–871, Nov 2022.

4. 신요섭, 김일민, 강성환, 이세훈, 박준현, 강재모, "AMFM : 금속 외관 결함의 준지도 분류에 특화된 AugMix 기반 FixMatch 알고리즘," 한국지능시스템학회 논문지, 제32권, 제5호, 424쪽–431쪽, 2022년 10월.
   Yo-Seob Shin, ll-Min Kim, Seong-Hwan Kang, Se-Hun Lee, Jun-Hyun Park, and Jae-Mo Kang, "AMFM: AugMix-empowered FixMatch for High-Performing Semi-Supervised Classification of Metal Surface Defects," Journal of Korean Institute of Intelligent Systems, vol. 32, no. 5, pp. 424–431, Oct. 2022.

5. 정득교, 이세훈, 강재모, "해외선물 스캘핑을 위한 강화학습 알고리즘의 성능 비교," 문화기술의 융합, 제8권, 제5호, 697쪽–703쪽, 2022년 9월.
   Deuk-Kyo Jung, Se-Hun Lee, and Jae-Mo Kang, "Performance Comparison of Reinforcement Learning Algorithms for Futures Scalping," The Journal of the Convergence on Culture Technology, vol. 8, no. 5, pp. 697–703, Sep. 2022.

6. 이세훈, 강성환, 신요섭, 최오규, 김시종, 강재모, "YOLO 기반 금속 외관 결함영역 검출," 한국지능시스템학회 논문지, 제32권, 제4호, 275쪽–285쪽, 2022년 8월.
   Se-Hun Lee, Seong-Hwan Kang, Yo-Seob Shin, Oh-Kyu Choi, Sijong Kim, and Jae-Mo Kang, "YOLO-Based Detection of Metal Surface Defects," Journal of Korean Institute of Intelligent Systems, vol. 32, no. 4, pp. 275–285, Aug. 2022.

7. 이세훈, 강성환, 신요섭, 최오규, 김시종, 강재모, "머신러닝 기반 금속외관 결함 검출 비교 분석," 한국정보통신학회논문지, 제26권, 제6호, 834쪽–841쪽, 2022년 6월.
   Se-Hun Lee, Seong-Hwan Kang, Yo-Seob Shin, Oh-Kyu Choi, Sijong Kim, and Jae-Mo Kang, "Comparative analysis of Machine-Learning Based Models for Metal Surface Defect Detection," Journal of the Korea Institute of Information and Communication Engineering, vol. 26, no. 6, pp. 834–841, Jun. 2022.

8. 임동우, 강재모, 강규민, "저복잡도 LoRa 심볼 검파 방식," 제46권, 제5호, 802쪽–805쪽, 한국통신학회논문지, 2021년 5월.  
   Dong-Woo Lim, Jae-Mo Kang, and Kyu-Min Kang, “A Low-Complexity Symbol Detection Scheme for LoRa Signals,” The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 5, pp. 802–805, May. 2021.

International Conference Papers

1. Chae Yoon Jung, Jae Mo Kang, and Dong In Kim, “Deep Learning based Channel Estimation for Full-Duplex Backscatter Communication Systems,” International Conference on Artificial Intelligence in Information and Communication, Feb. 2023, pp. 347–352.

2. Byungjo Kim, Jae-Mo Kang, Hyung-Myung Kim, and Joohyun Lee, “Energy Efficiency Optimization in Multi-Antenna Wireless Powered Communication network,” Information and Communication Technology Convergence, Oct. 2016, pp. 756–758.

3. Byungjo Kim, Jae-Mo Kang, Hyung-Myung Kim, and Joohyun Lee, “Max-Min Energy-Efficiency Optimization in Wireless Powered Communication Network with Harvest-Then-Transmit Protocol,” IT Convergence and Security, Sep. 2016, pp. 1–5.

4. Changdon In, Jae-Mo Kang, and Hyung-Myung Kim, “Source and Relay Precoder Designs to Maximize Sum Rate in Two-Way Relay System with Multiple Sources,” IEEE Vehicular Technology Conference, May. 2015, pp. 1–5.

5. Jae-Mo Kang, Changdon In, and Hyung-Myung Kim, “Detection of Pilot Contamination Attack for Multi-Antenna Based Secrecy Systems,” IEEE Vehicular Technology Conference, May. 2015, pp. 1–5.

6. Jae-Hwan Lee, Jae-Mo Kang, and Hyung-Myung Kim, “Secure Transmission for Multi-Antenna Two-Way Relay Cellular Networks with No Eavesdropper’s CSI,” International Conference on Telecommunications, Apr. 2015, pp. 214–218.

7. Jae-Mo Kang, Jae-Hwan Lee, and Hyung-Myung Kim, “Training-Based Estimation of Spatially Correlated Channels in AF MIMO Multi-Relay Systems using LMMSE Criterion,” International Conference on Telecommunications, Apr. 2015, pp. 358–362.

8. Changdon In, Dong-Woo Lim, Jae-Mo Kang, Jae-Hwan Lee, Hyung-Myung Kim, Seongdo Kim, and Cheonsoo Kim, “Human Detection Based on the Condition Number in the Non-Stationary Clutter Environment using UWB Impulse Radar,” Asia-Pacific Microwave Conference, Nov. 2013, pp. 1006–1008.

9. Jae-Mo Kang, Dong-Woo Lim, Jae-Hwan Lee, Changdon In, Hyung-Myung Kim, Sung-Chul Woo, and Cheonsoo Kim, “Reliable Estimation of Respiration Rate using UWB Impulse Radar,” Asia-Pacific Microwave Conference, Nov. 2013, pp. 997–999.

Domestic Conference Papers

1. 박채원, 성민규, 강재모,  “다중 도메인 이미지 생성 성능 향상을 위한 Self-Attention 메커니즘 기반 적대적 생성 네트워크,” 한국지능시스템학회 2023년도 춘계학술대회(KIIS Spring Conference 2023), 2023년 4월.

2. 하상준, 강재모, “모델 앙상블을 활용한 유전체 변이 정보 기반 품종 구분 모델링,” 한국지능시스템학회 2023년도 춘계학술대회(KIIS Spring Conference 2023), 2023년 4월.

3. 박채원, 성민규, 강재모, “다중 도메인 이미지 생성 성능 향상을 위한 Self-Attention 메커니즘 기반 적대적 생성 네트워크,” 한국지능시스템학회 2023년도 춘계학술대회(KIIS Spring Conference 2023), 2023년 4월.

4. 최미희, 강재모, “메타 러닝을 활용한 퓨샷 분류기 성능 검증,” 제3회 한국 인공지능 학술대회 (3rd Korea Artificial Intelligence Conference), 2022년 9월.

5. Sijia Li, Jae-Mo Kang, “TAU-net: Convolution Networks for Road segmentation,” JCCI 2022 (The 32nd Joint Conference on Communications and Information), Apr. 2022.

6. 성민규, 강재모, “무손실 압축 기법을 이용한 딥러닝 경량화 기법,” JCCI 2022 (제32회 통신정보 합동학술대회), 2022년 4월.

7. 김영록, 강재모, “드론 식별을 위한 딥러닝 기반 하향링크 빔형성 알고리즘,” JCCI 2022 (제32회 통신정보 합동학술대회), 2022년 4월.

8. 박준현, 강재모, “드론 식별을 위한 딥러닝 기반 상향링크 송신 전력 할당,” JCCI 2022 (제32회 통신정보 합동학술대회), 2022년 4월.

9. Jihoon Park and Jae-Mo Kang, “Federated Learning and Its Applications,” CKAIA2020 (The 2nd Conference of Korean Artificial Intelligence Association), Aug. 2020.

10. 인창돈, 임동우, 강재모, 이재환, 김형명, 김성도, 김천수, “Performance Comparisons of CFAR Detectors in Ultra-wideband Impulse Radar System,” 한국군사과학기술학회 2013년 종합학술대회, 2013년 7월.

11. 강재모, 임동우, 김형명, 우성철, 김천수, "Stride Rate Estimation for Walking Human in Ultra-Wideband Impulse Radar System,” 한국군사과학기술학회 2013년 종합학술대회, 2013년 7월.

12. 강재모, 임동우, 김형명, 박필재, 김성도, 우성철, 김천수, “초광대역 임펄스 레이더 환경에서 사람의 보행률 추정 방법,” 제20회 지상무기 학술대회, 2012년 12월.