Results 71 to 80 of about 18,989 (190)

Brain‐RetinaNet: Detection of Brain Tumour Using an Improved RetinaNet in Magnetic Resonance Imaging

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Brain tumours disrupt the normal functioning of the brain and, if left untreated, can invade surrounding tissues, blood vessels, and nerves, posing a severe threat. Consequently, early detection is crucial to prevent tragic outcomes. Distinguishing brain tumours through manual detection poses a significant challenge given their diverse ...
Rashid Iqbal, Rabbia Mahum, Mohamed Sharaf, Javed Ali Khan   +3 more
wiley   +1 more source

Deformable ConvNet with Aspect Ratio Constrained NMS for Object Detection in Remote Sensing Imagery

Remote Sensing, 2017
Convolutional neural networks (CNNs) have demonstrated their ability object detection of very high resolution remote sensing images. However, CNNs have obvious limitations for modeling geometric variations in remote sensing targets.
Zhaozhuo Xu, Xin Xu, Lei Wang, Rui Yang, Fangling Pu   +4 more
doaj   +1 more source

Lightweight Hybrid Wafer Defect Pattern Network Based on Feedforward Efficient Attention

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT With the increase of semiconductor integration density, in order to cope with the increase of wafer defect complexity and types, especially the low recognition accuracy of overlapping mixed defects and unknown wafer defects, this study proposes a lightweight model for wafer defect detection called LightWMNet.
Zhiqiang Hu, Yiquan Wu
wiley   +1 more source

An Improved Splicing Localization Method by Fully Convolutional Networks

IEEE Access, 2018
Liu and Pun proposed a method based on fully convolutional network (FCN) and conditional random field (CRF) to locate spliced regions in synthesized images from different source images. However, their work has two drawbacks: 1) FCN often smooths detailed
Beijing Chen, Xiaoming Qi, Yiting Wang, Yuhui Zheng, Hiuk Jae Shim, Yun-Qing Shi   +5 more
doaj   +1 more source

FCN-Based Carrier Signal Detection in Broadband Power Spectrum

IEEE Access, 2020
Carrier signal detection has been a problem for a long time, which is the first step for blind signal processing. In this paper, we propose a new method for carrier signal detection in the broadband power spectrum based on the fully convolutional network
Hao Huang, Jian-Qing Li, Jiao Wang, Hong Wang   +3 more
doaj   +1 more source

ParseNet: Looking Wider to See Better [PDF]

, 2015
We present a technique for adding global context to deep convolutional networks for semantic segmentation. The approach is simple, using the average feature for a layer to augment the features at each location.
Berg, Alexander C., Liu, Wei, Rabinovich, Andrew   +2 more
core  

Tibetan Data Augmentation via GAN‐Based Handwritten Text Generation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Increased awareness of Tibetan cultural preservation, along with technological advancements, has led to significant efforts in academic research on Tibetan. However, the structural complexity of the Tibetan language and limited labeled handwriting data impede advancements in Optical Character Recognition (OCR) and other applications.
Dorje Tashi, Bingtian Chen, Tianying Sheng, Yongbin Yu, Xiangxiang Wang, Jin Zhang, Lobsang Yeshi, Rinchen Dongrub, Thupten Tsering, Nyima Tashi   +9 more
wiley   +1 more source

Ship Detection Based on Improved R-FCN

Jisuanji kexue yu tansuo, 2020
Aiming at the problem of detecting different sizes and types of ships in complex sea conditions, a ship detection method based on deep learning is proposed, which is mainly for the improvement of regional fully convolutional networks (R-FCN).
HUANG Zhijun, SANG Qingbing
doaj   +1 more source

Textile and colour defect detection using deep learning methods

Coloration Technology, EarlyView.
Abstract Recent advances in deep learning (DL) have significantly enhanced the detection of textile and colour defects. This review focuses specifically on the application of DL‐based methods for defect detection in textile and coloration processes, with an emphasis on object detection and related computer vision (CV) tasks.
Hao Cui, Abdel‐Fattah Seyam, Renzo Shamey   +2 more
wiley   +1 more source

Brain tissue classification in hyperspectral images using multistage diffusion features and transformer

Journal of Microscopy, EarlyView.
Abstract Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning.
Neetu Sigger, Tuan T. Nguyen, Gianluca Tozzi   +2 more
wiley   +1 more source