公开(公告)号：US20230316511A1

公开(公告)日：2023-10-05

申请号：US18176497

申请日：2023-03-01

Applicant: HTC Corporation

Inventor： Chen-Han TSAI ,  Yu-Shao PENG

IPC: G06T7/00 ,  G06T5/50 ,  G06V10/25 ,  G06V10/44 ,  G06V10/764 ,  G06V10/771 ,  G06V10/82

CPC classification number: G06T7/0012 ,  G06T5/50 ,  G06V10/25 ,  G06V10/454 ,  G06V10/764 ,  G06V10/771 ,  G06V10/82 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20016 ,  G06T2207/20221 ,  G06T2207/30096 ,  G06V2201/07

Abstract: A medical image detection system includes a memory and a processor. The processor is configured to execute the neural network model stored in the memory. The neural network model includes a feature extractor, a feature pyramid network, a first output head and a second output head. The feature extractor is configured for extracting intermediate tensors from a medical image. The feature pyramid network is associated with the feature extractor. The feature pyramid network is configured for generating multi-resolution feature maps according to the intermediate tensors. The first output head is configured for generating a global prediction according to the multi-resolution feature maps. The second output head is configured for generating local predictions according to the multi-resolution feature maps. The processor is configured to generate output information based on the medical image, the global prediction and the local predictions.

公开(公告)号：US20240160660A1

公开(公告)日：2024-05-16

申请号：US18503197

申请日：2023-11-07

Applicant: HTC Corporation

Inventor： Chen-Han TSAI ,  Yu-Shao PENG

IPC: G06F16/55 ,  G06F18/241

CPC classification number: G06F16/55 ,  G06F18/241

Abstract: A data classification method, for classifying unlabeled images into an inlier data set or an outlier data set, include following steps. The unlabeled images are obtained. An assigned inlier image is selected among the unlabeled images. A similarity matrix is computed and the similarity matrix includes first similarity scores of the unlabeled images relative to the assigned inlier image. Each of the unlabeled images is classified into an inlier data set or an outlier data set according to the similarity matrix, so as to generate inlier-outlier predictions of the unlabeled images.

公开(公告)号：US20250077552A1

公开(公告)日：2025-03-06

申请号：US18818623

申请日：2024-08-29

Applicant: HTC Corporation

Inventor： Chen-Han TSAI ,  Yu-Shao PENG

IPC: G06F16/332 ,  G06F16/35

Abstract: A data classification method includes following steps. Text samples are obtained from a dataset. The text samples are converted into text embeddings in a semantic space. An outlier-inlier ranking of the text samples is generated based on an outlier detection algorithm according to distances between the text embeddings in the semantic space. Partial samples are selected from the text samples according to the outlier-inlier ranking. A manual input command is received to assign manual-input labels on the partial samples. A prompt message is generated according to the partial samples with the manual-input labels and unlabeled samples of the text samples. The prompt message is provided to a generative pre-trained transformer model for generating inlier-outlier prediction labels about the unlabeled samples.