Anabranch network for camouflaged object segmentation [PDF]
Computer Vision and Image Understanding, 2019 Camouflaged objects attempt to conceal their texture into the background and discriminating them from the background is hard even for human beings. The main objective of this paper is to explore the camouflaged object segmentation problem, namely, segmenting the camouflaged object(s) for a given image. This problem has not been well studied in spite of
Akihiro Sugimoto +2 more
exaly +3 more sources
Semantic Segmentation Algorithm Combined with Edge Detection [PDF]
Jisuanji gongcheng, 2021 To address the fuzzy and inaccurate target edges in semantic segmentation,a semantic segmentation network combined with edge detection is proposed.The network consists of an edge detection network and a semantic segmentation network.The edge detection ...
WANG Nan, HOU Zhiqiang, ZHAO Mengqi, YU Wangsheng, MA Sugang
doaj +1 more source
Clothing Image Segmentation Network Based on Improved Deeplab v3+ [PDF]
Jisuanji gongcheng, 2022 To solve the problems of rough clothing edge segmentation, unsatisfactory segmentation accuracy, and insufficient deep semantic feature extraction in clothing image segmentation, the Coordinate Attention(CA) mechanism and Semantic Feature Enhancement ...
HU Xinrong, GONG Chuang, ZHANG Zili, ZHU Qiang, PENG Tao, HE Ruhan
doaj +1 more source
Fast Panoptic Segmentation Network [PDF]
IEEE Robotics and Automation Letters, 2020 In this work, we present an end-to-end network for fast panoptic segmentation. This network, called Fast Panoptic Segmentation Network (FPSNet), does not require computationally costly instance mask predictions or merging heuristics. This is achieved by casting the panoptic task into a custom dense pixel-wise classification task, which assigns a class ...
Daan de Geus +2 more
openaire +2 more sources
Ultrasonic Thyroid Nodule Segmentation Based on Segmentation Adversarial Network
Taiyuan Ligong Daxue xuebao, 2023 An ultrasonic thyroid nodule segmentation model based on conditional segmentation adversarial network (cSegAN) was proposed to achieve more accurate segmentation of thyroid nodules.
Junxia WU +3 more
doaj +1 more source
Tracking the Rhythm: Pansori Rhythm Segmentation and Classification Methods and Datasets
Applied Sciences, 2022 This paper presents two methods to understand the rhythmic patterns of the voice in Korean traditional music called Pansori. We used semantic segmentation and classification-based structural analysis methods to segment the seven rhythmic categories of ...
Yagya Raj Pandeya +2 more
doaj +1 more source
Weakly Supervised Building Semantic Segmentation Based on Spot-Seeds and Refinement Process
Entropy, 2022 Automatic building semantic segmentation is the most critical and relevant task in several geospatial applications. Methods based on convolutional neural networks (CNNs) are mainly used in current building segmentation.
Khaled Moghalles +2 more
doaj +1 more source
Assessing DER network cybersecurity defences in a power-communication co-simulation environment
IET Cyber-Physical Systems, 2020 Increasing penetrations of interoperable distributed energy resources (DER) in the electric power system are expanding the power system attack surface.
Jay Johnson +6 more
doaj +1 more source
Bone tumor examination based on FCNN-4s and CRF fine segmentation fusion algorithm
Journal of Bone Oncology, 2023 Background and objective: Bone tumor is a kind of harmful orthopedic disease, there are benign and malignant points. Aiming at the problem that the accuracy of the existing machine learning algorithm for bone tumor image segmentation is not high, a bone ...
Shiqiang Wu +6 more
doaj +1 more source
Segmentation of retinal fluid based on deep learning: application of three-dimensional fully convolutional neural networks in optical coherence tomography images [PDF]
International Journal of Ophthalmology, 2019 AIM: To explore a segmentation algorithm based on deep learning to achieve accurate diagnosis and treatment of patients with retinal fluid. METHODS: A two-dimensional (2D) fully convolutional network for retinal segmentation was employed.
Meng-Xiao Li +6 more
doaj +1 more source