Results 41 to 50 of about 379 (188)

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam, Basit Raza, Muhammad Faheem, Aadil Raza   +3 more
wiley   +1 more source

Robust steganographic framework for securing sensitive healthcare data of telemedicine using convolutional neural network

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Data is the key element that runs the modern society. Large amounts of data are being released day by day as a result of many activities. The digital data is transferred through the Internet which may be vulnerable to attacks while transmitting. Especially, the medical data is observed to be of at most importance.
Rupa Ch, Venkayya Yadlapalli, Suhana Sulthana Sk, G. Thippa Reddy, Sandeep Kautish   +4 more
wiley   +1 more source

DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu, Xuanyu Zhang, Xiandong Meng, Jian Zhang   +3 more
wiley   +1 more source

CDFNet: Cross‐Modal Deep Fusion for Monocular 3D Semantic Scene Completion

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Semantic scene completion (SSC) aims to predict the semantic occupancy and geometry of 3D scenes. Recently, most studies focus on camera‐based approaches due to the rich visual cues of images and the cost‐effectiveness of cameras. However, these methods usually lack efficient fusion and fine‐grained processing of cross‐modal semantic ...
Xianjing Cheng, Lintai Wu, Jie Wen, Tianhao Peng, Yong Xu, Zairong Wei   +5 more
wiley   +1 more source

Efficient Masked Autoencoder for Birdsong Representation with Applications on Wild Bird Species Classification

Integrative Zoology, EarlyView.
Research on mosquito feeding preferences and the malaria parasites they transmit is essential for understanding the interactions between hosts, vectors, and parasites. In this study, vertebrate hosts were identified in 72 mosquitoes. Most blood meals (58.7%) came from birds, representing 25 species, while 40.0% came from mammals (13 species), and 1.3 ...
Qin Zhang, Shipeng Hu, Hengrui Wang, Jizheng Yi, Guoxiong Zhou, Xiangyu Shen, Weixiong Peng, Zhishu Xiao, Aibin Chen   +8 more
wiley   +1 more source

NePO: Neural Point Octrees for Large‐Scale Novel View Synthesis

Computer Graphics Forum, EarlyView.
We introduce Neural Point Octrees (NePOs), a scalable radiance field representation that organises point clouds hierarchically for efficient optimisation and rendering of large scale scenes. NePOs enable level of detail selection, joint refinement of appearance and camera poses, and real‐time rendering of hundreds of millions of points.
Noah Lewis, Darius Rückert, Marc Stamminger, Linus Franke   +3 more
wiley   +1 more source

Adaptive Sampling for BRDF Acquisition

Computer Graphics Forum, EarlyView.
We propose a data‐driven adaptive sampling strategy that predicts the optimal sampling pattern and count for BRDF acquisition from a single image, reducing capture time while preserving quality. Abstract The bidirectional reflectance distribution function (BRDF) describes the ratio of incoming radiance to outgoing radiance for all possible pairs of ...
Behnaz Kavoosighafi, Saghi Hajisharif, Jonas Unger, Ehsan Miandji   +3 more
wiley   +1 more source

Robo‐Saber: Generating and Simulating Virtual Reality Players

Computer Graphics Forum, EarlyView.
Abstract We present the first motion generation system for playtesting virtual reality (VR) games. Our player model generates VR headset and handheld controller movements from in‐game object arrangements, guided by style reference gameplay examples. We train on the large BOXRR‐23 dataset and apply our framework on the popular VR game Beat Saber.
N. H. Kim, M. J. Liu, J. Lehtinen, P. Hämäläinen, J. F. O'Brien, X. B. Peng   +5 more
wiley   +1 more source

VQ‐Style: Disentangling Style and Content in Motion with Residual Quantized Representations

Computer Graphics Forum, EarlyView.
Abstract Human motion data is inherently rich and complex, containing both semantic content and subtle stylistic features that are challenging to model. We propose a novel method for effective disentanglement of the style and content in human motion data to facilitate style transfer.
Fatemeh Zargarbashi, Dhruv Agrawal, Jakob Buhmann, Martin Guay, Stelian Coros, Robert W. Sumner   +5 more
wiley   +1 more source

Authoring Terrestrial Planets with Diffusion Models

Computer Graphics Forum, EarlyView.
Abstract To support the design and subsequent generation of terrestrial planets for use in the creative media, we propose a solution that employs a generative model trained on satellite data from planetary bodies with a defined solid surface, such as the Earth and Mars.
Oliver Borg, James Gain, Éric Guérin, Adrien Peytavie, Marie‐Paule Cani, Eric Galin, Guillaume Cordonnier   +6 more
wiley   +1 more source