3 citations · 3 across the 2 of their papers we have counts for
5 papers
Adapting SQuaRE for Quality Assessment of Artificial Intelligence Systems
Hiroshi Kuwajima, Fuyuki Ishikawa
More and more software practitioners are tackling towards industrial applications of artificial intelligence (AI) systems, especially those based on machine learning (ML). However,…
Engineering problems in machine learning systems
Hiroshi Kuwajima, Hirotoshi Yasuoka, Toshihiro Nakae
Fatal accidents are a major issue hindering the wide acceptance of safety-critical systems that employ machine learning and deep learning models, such as automated driving vehicles…
Improving Transparency of Deep Neural Inference Process
Hiroshi Kuwajima, Masayuki Tanaka, Masatoshi Okutomi
Deep learning techniques are rapidly advanced recently, and becoming a necessity component for widespread systems. However, the inference process of deep learning is black-box, and…
Open Problems in Engineering and Quality Assurance of Safety Critical Machine Learning Systems
Hiroshi Kuwajima, Hirotoshi Yasuoka, Toshihiro Nakae
Fatal accidents are a major issue hindering the wide acceptance of safety-critical systems using machine-learning and deep-learning models, such as automated-driving vehicles. Qual…
Network Analysis for Explanation
Hiroshi Kuwajima, Masayuki Tanaka
Safety critical systems strongly require the quality aspects of artificial intelligence including explainability. In this paper, we analyzed a trained network to extract features w…