広島大学 - ‪‪引用: 1 件‬‬ - ‪Object Detection‬

Shinji Uchinoura, Takio Kurita: Improved Head and Data Augmentation to Reduce Artifacts at Grid Boundaries in Object Detection. IEICE Trans. Inf. Syst.

Works at 株式会社パル技研 · Studied at 岡山大学 · Went to 宮崎県立宮崎南高等学校 · Lives in Takamatsu, Kagawa · From Miyazaki, Miyazaki ...

Abstract. This paper proposes a two-step detector called segmented object detection, whose performance is improved by masking the background region.

Request PDF | On Aug 21, 2022, Shinji Uchinoura and others published Graph Laplacian Regularization based on the Differences of Neighboring Pixels for ...

We propose a regularization that penalizes the errors in the spatial structure with a graph composed of the differences between neighboring pixels.

Jan 1, 2024 · Improved Head and Data Augmentation to Reduce Artifacts at Grid Boundaries in Object Detection Shinji UCHINOURA · Takio KURITA Publication

This paper proposes a two-step detector called segmented object detection, whose performance is improved by masking the background region.

Therefore, this paper proposes two approaches focused on the grid boundary to improve this weak point of current object detection methods. One is the Sub-Grid ...