https://scholar.dgist.ac.kr/handle/20.500.11750/10133 2026-08-13T09:20:25Z https://scholar.dgist.ac.kr/handle/20.500.11750/60583 Title: 두둑 성형 장치, 및 자율 주행 경로 생성 방법 Author(s): 박지호; 한중희 Abstract: 본 발명은, 밭의 경계점을 이용하여 두둑 성형 로봇의 자율 주행 경로 생성하기 위한 방안에 관한 것이다. https://scholar.dgist.ac.kr/handle/20.500.11750/60565 Title: 인공지능 모델의 학습을 위한 학습데이터의 불균형을 개선하는 방법 및 장치 Author(s): 안영선; 이충희 Abstract: 일 측면에 따른 인공지능 모델의 학습을 위한 학습데이터의 불균형을 개선하는 방법은, 제1 학습영상을 언더 샘플링하는 단계; 및 상기 언더 샘플링의 결과를 반영하여 제2 학습영상을 오버 샘플링하는 단계;를 포함하고, 상기 언더 샘플링하는 단계는, 상기 제1 학습영상을 그룹으로 묶어 제1 학습그룹을 생성하는 단계; 상기 제1 학습그룹을 하나씩 입력하여 제1 인공지능 모델을 학습시키고 제1 점수를 산출하는 단계; 상기 제1 점수가 가장 높은 제1 학습그룹에 상기 제1 점수가 다음으로 높은 제1 학습그룹을 순서대로 하나씩 추가하여 상기 제1 인공지능 모델을 학습시키고 제2 점수를 산출하는 단계; 및 상기 제2 점수가 미리 설정된 값에 해당하는 상기 제1 학습그룹을 언더 샘플링 학습그룹으로 선택하는 단계;를 포함하고, 상기 오버 샘플링하는 단계는, 상기 제2 학습영상에 데이터 증강 기법을 적용하여 제2 학습그룹을 생성하는 단계; 상기 언더 샘플링 학습그룹, 상기 제2 학습영상 및 상기 제2 학습그룹을 입력하여 제2 인공지능 모델을 학습시키고 제3 점수를 산출하는 단계; 및 상기 산출된 제3 점수가 가장 높은 제2 학습그룹을 오버 샘플링 학습그룹으로 선택하는 단계;를 포함한다. https://scholar.dgist.ac.kr/handle/20.500.11750/60463 Title: Social economy and social innovation across diverse contexts: City-level findings from Korea, Italy, and Poland Author(s): Yun, JinHyo Joseph; Zhao, Xiaofei; Koo, Inhyouk; Del Gaudio, Giovanna; Della Corte, Valentina; Turon, Katarzyna; Yigitcanlar, Tan Abstract: This study investigates the contextual foundations that shape the characteristics and dynamics of the social economy and its approach to social open innovation across three countries-South Korea, Italy, and Poland. Specifically, it examines three core dimensions: the agenda pursued, the organizational types involved, and the sustainability of social economy actors. Addressing significant gaps in the literature, the study poses two research questions: (a) How do political, economic, and cultural contexts influence the development of the social economy and social open innovation in each country? (b) In what ways do these contextual differences affect organizational forms, strategic agendas, and long-term sustainability? Employing a comparative, multi-method qualitative approach-including in-depth interviews and participatory observation-the findings reveal stark contrasts across the three countries. Italy's social economy is mature and economically grounded, Poland's is culturally driven yet emergent, and South Korea's is politically shaped but organizationally fragile. These differences suggest that context plays a critical role in defining the evolution, focus, and resilience of the social economy and its potential for fostering socially oriented innovation. The study contributes to grounded theory development by offering a comparative framework that links contextual foundations with the trajectory of social innovation across diverse urban settings. 2026-05-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60455 Title: Entropy-Gated Prediction Agreement for Two-View Video Action Recognition Author(s): Park, Young-Jin; Cho, Hui-Sup Abstract: Human action recognition (HAR) often struggles to capture important temporal cues distributed across an entire video when relying solely on a single sampled clip. To overcome this limitation, this study proposes a framework that constructs two temporal views from the same video and explicitly learns the prediction consistency between them. Specifically, the prediction-level agreement (AG) loss was introduced to align the class probability distributions of the two views. In addition, conditional gating was applied to adaptively control the contribution of AG loss according to the sample-wise prediction confidence, thereby reducing unstable alignment in temporally ambiguous or information-insufficient segments. The proposed framework was evaluated using both convolutional neural network (CNN)- and Transformer-based backbones on three representative action-recognition benchmark datasets, and it generally improved the performance over the single-view baseline across backbone-dataset combinations. Further empirical analyses, including training behavior, motion magnitude, temporal prediction stability, and qualitative case studies, were conducted to examine the effectiveness and behavior of the proposed two-view framework from multiple perspectives. 2026-06-30T15:00:00Z