Robust Shelf Monitoring Using Supervised Learning for Improving On-Shelf Availability in Retail Stores

This paper proposes a method to robustly monitor shelves in retail stores using supervised learning for improving on-shelf availability. To ensure high on-shelf availability, which is a key factor for improving profits in retail stores, we focus on understanding changes in products regarding increases/decreases in product amounts on the shelves. Our method first detects changed regions of products in an image by using background subtraction followed by moving object removal. It then classifies the detected change regions into several classes representing the actual changes on the shelves, such as “product taken (decrease)” and “product replenished/returned (increase)”, by supervised learning using convolutional neural networks. It finally updates the shelf condition representing the presence/absence of products using classification results and computes the product amount visible in the image as on-shelf availability using the updated shelf condition. Three experiments were conducted using two videos captured from a surveillance camera on the ceiling in a real store. Results of the first and second experiments show the effectiveness of the product change classification in our method. Results of the third experiment show that our method achieves a success rate of 89.6% for on-shelf availability when an error margin is within one product. With high accuracy, store clerks can maintain high on-shelf availability, enabling retail stores to increase profits

Polymer-derived organoamine-functionalized amorphous silica materials for CO₂ capture

International audienc

Amine-functionalized polycarbosilane hybrids for CO2-selective membranes

International audienc

Adrenal Hemangioma: A Case of Retroperitoneal Tumor

Introduction. Adrenal hemangioma is a rare disease, with only some 60 cases reported previously. Due to the difficulty of the preoperative diagnosis of adrenal hemangioma, almost all of the cases were diagnosed by a histopathological analysis of surgical specimens. Case Presentation. A 52-year-old man was referred to our department for further examination of his left retroperitoneal tumor. He had received hemodialysis due to chronic renal failure resulting from membranous nephropathy. Computed tomography revealed a mass around his left hilum. Magnetic resonance imaging (MRI) and positron-emission tomography (PET)-CT were unable to confirm or deny malignancy, and tumor markers, including CEA and CA19-9, showed slight elevation. His tumor grew from 38 mm to 54 mm in diameter in 7 months of follow-up. We therefore planned retroperitoneal tumor resection with left nephrectomy. Histopathologically, hyperplastic small vessels with hemorrhaging and denaturation were seen. The endothelial cells showed no variants or division of the nucleus. Based on this diagnosis, no further therapy was performed. He has had no recurrence in the eight months since the surgery. Conclusion. We herein report a rare case of adrenal hemangioma

Measurement of double-differential neutron yields for iron, lead, and bismuth induced by 107-MeV protons for research and development of accelerator-driven systems

For the research and development of accelerator-driven systems (ADSs) and fundamental ADS reactor physics research using the Kyoto University Critical Assembly combined with the fixed-field alternating gradient (FFAG) accelerator, we are conducting a series of experiments on double-differential neutron yields using the FFAG accelerator at Kyoto University. This paper presents an overview of the experiments together with preliminary results