Zobrazeno 1 - 10
of 240
pro vyhledávání: '"Hotta, Kazuhiro"'
We propose a Ground IoU (Gr-IoU) to address the data association problem in multi-object tracking. When tracking objects detected by a camera, it often occurs that the same object is assigned different IDs in consecutive frames, especially when objec
Externí odkaz:
http://arxiv.org/abs/2409.03252
Autor:
Sakai, Taigo, Hotta, Kazuhiro
Deep learning has excelled in image recognition tasks through neural networks inspired by the human brain. However, the necessity for large models to improve prediction accuracy introduces significant computational demands and extended training times
Externí odkaz:
http://arxiv.org/abs/2408.13291
Autor:
Mitsuoka, Hinako, Hotta, Kazuhiro
Semantic segmentation of microscopy cell images by deep learning is a significant technique. We considered that the Transformers, which have recently outperformed CNNs in image recognition, could also be improved and developed for cell image segmenta
Externí odkaz:
http://arxiv.org/abs/2408.12974
There has been a lot of recent research on improving the efficiency of fine-tuning foundation models. In this paper, we propose a novel efficient fine-tuning method that allows the input image size of Segment Anything Model (SAM) to be variable. SAM
Externí odkaz:
http://arxiv.org/abs/2408.12406
Facial landmark detection is an essential technology for driver status tracking and has been in demand for real-time estimations. As a landmark coordinate prediction, heatmap-based methods are known to achieve a high accuracy, and Lite-HRNet can achi
Externí odkaz:
http://arxiv.org/abs/2308.12133
Autor:
Kato, Sota, Hotta, Kazuhiro
We propose a novel loss function for imbalanced classification. LDAM loss, which minimizes a margin-based generalization bound, is widely utilized for class-imbalanced image classification. Although, by using LDAM loss, it is possible to obtain large
Externí odkaz:
http://arxiv.org/abs/2306.09132
Endoscopic Ultrasound-Fine Needle Aspiration (EUS-FNA) is used to examine pancreatic cancer. EUS-FNA is an examination using EUS to insert a thin needle into the tumor and collect pancreatic tissue fragments. Then collected pancreatic tissue fragment
Externí odkaz:
http://arxiv.org/abs/2304.10791
Autor:
Kato, Sota, Hotta, Kazuhiro
Semantic segmentation of microscopic cell images using deep learning is an important technique, however, it requires a large number of images and ground truth labels for training. To address the above problem, we consider an efficient learning framew
Externí odkaz:
http://arxiv.org/abs/2304.07991
Anomaly detection is an important problem in computer vision; however, the scarcity of anomalous samples makes this task difficult. Thus, recent anomaly detection methods have used only normal images with no abnormal areas for training. In this work,
Externí odkaz:
http://arxiv.org/abs/2210.07548
Autor:
Kato, Sota, Hotta, Kazuhiro
Dice loss is widely used for medical image segmentation, and many improvement loss functions based on such loss have been proposed. However, further Dice loss improvements are still possible. In this study, we reconsidered the use of Dice loss and di
Externí odkaz:
http://arxiv.org/abs/2207.07842